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Dynamic Modelling, Analysis and Design of Smart
Hybrid Energy Storage System for Off-grid
Photovoltaic Power Systems
by
Wenlong JING
A dissertation submitted to the Swinburne University of Technology in support of an
application for the degree of Doctor of Philosophy in Engineering
Faculty of Engineering, Computing and Science
Swinburne University of Technology
Sarawak Campus
January 2019
Dedicated to…
my beloved Parents, Teachers, Partner, Family & Friends
Abstract
Battery technology has been widely utilized in different energy storage
applications. However, limitations and challenges such as heat dissipation, low power
density, unsatisfactory lifetime characteristics, environmental impacts, and high cost
hinder its development in many key areas, for instance, the residential energy storage
applications. To address the issue of the short service life of the battery, hybrid energy
storage system (HESS) of various designs have been reported in the literature. However
the limited focus has been put on the case of the stand-alone residential energy system,
especially for remote rural electrification. This thesis aims at proposing suitable battery-
supercapacitor HESS designs and control strategies that can effectively extend the
battery service lifetime via mitigating its operation stress, thereby realizing the cost
reduction on the installing construction and operating costs of the stand-alone
photovoltaic (PV) power system. For such systems that is planned to be installed in
rural areas, potential suitable battery-supercapacitor HESSs are designed and discussed.
To leverage on existing infrastructure in installed standalone PV-battery power system,
novel smart supercapacitor/Li-ion HESS plug-in module (SHESS) is proposed to relieve
the main battery operation stress. Theoretical analysis and numerical simulations for the
designed HESSs and the SHESS are conducted, and their effectiveness in mitigating
battery stress are investigated and compared via pulse load testing and case studies with
actual data of solar irradiance and load profile from a remote community in Sarawak,
Malaysia. A battery health cost model is formulated to qualitatively evaluate the impact
of battery current on battery health, thus enabling the estimation of service life
improvement as well as the assessment on the economic impact of the remote stand-
alone microgrid. A down-scaled prototype of the proposed HESS is designed and
developed to verify the theoretical analysis and analytical findings. Experiments have
been carried out to test the feasibility and performance of the proposed system in terms
of power-sharing capability in stand-alone PV power system operations. The
experimental results demonstrate the feasibility of the proposed HESSs in retrofitting
existing installed PV power systems and support the theoretical analysis and simulation
outcomes.
Acknowledgments
The journey to achieve the Ph.D. is full of obstacles, challenges, and happiness, which
will always remind me of the importance of humility, exploration and lifelong learning.
The completion of the dissertation marks the end of such an eventful journey and many
people I am willing to offer my sincerest thanks. Firstly, I would like to express my
sincere gratitude to my principal supervisor, Dr. Chean Hung Lai, for his invaluable
inspiration, continuous guidance, constructive criticism and support throughout this
research. This dissertation would not have been possible without his help, support,
resolute dedication, and patience. His expert advice and unsurpassed knowledge of the
various fields of electrical energy systems has always provided me an endless supply of
idea to move to the next step and complete this dissertation.
I also feel privileged that my Ph.D. study was conducted under the supervision of co-
supervisors, Prof. Wallace Wong Shung Hui and Prof. M. L. Dennis Wong. Their
constant encouragement, illuminating guidance, and research suggestions were indeed
essential for the completion of this study and dissertation. Meanwhile, I would like to
thank all colleagues at the Research Laboratory of Swinburne University of Technology
Sarawak Campus for their various forms of help and support so that I can achieve my
research goals. To my best friends and research partners in Malaysia, Dr. Pan, Ms. Jong
Bih Fei, Dr. Liew Lin Shen, Mr. Tay Jia Jun, Abdul Kadir Muhammad Lawan, Mr.
Derrick Ling Kuo Xiong, Mr. Chang Zhi Hao, Dr. Wong Wei Jing and Dr. Chong
Nguan Soon, the memorable times, laughs, countless discussions, sharing, etc that we
have will be the lifelong treasures and I would never forget.
To my dear life partner, Yun Wang, appreciate and value her everlasting love and
understanding so that I could fully focus on my study. I also extend my utmost gratitude
to my dearest teachers, family, and friends, for their encouragement and assistance all
these years. Last but the most important, I would like to give special thanks to my
mother and father for their unconditional support both financially and morally, the grace
of raising me up and deep love, which is the most precious thing in my life.
Declaration
I hereby declare that, to the best of my knowledge, this thesis contains no material
which has been accepted for the award to the candidate of any other degree or
qualification in this, or any other University and contains no material previously
published or written by another person except where due reference is made in the text of
this thesis. Furthermore, any idea, technique, quotation, or any other material from other
people’s work included in this thesis, published or otherwise, are fully acknowledged in
accordance with the standard referencing practices.
----------------------------------
Wenlong JING
January 2019
Publications arising from this study
Journal Papers
Wenlong Jing, Chean Hung Lai, Wallace SH Wong, and ML Dennis Wong, "A comprehensive study of Battery-SC hybrid ESS for stand-alone PV power system in rural electrification." Applied Energy, Volume 224, May 2018, Pages 340-356.
Wenlong Jing, Chean Hung Lai, Wallace SH Wong, and ML Dennis Wong, “Dynamic Power Allocation of Battery-SC Hybrid Energy Storage for Stand-alone PV microgrid Applications”, Sustainable Energy Technologies and Assessments, Volume 22, August 2017, Pages 55-64, ISSN 2213-1388.
Wenlong Jing, Chean Hung Lai, Wallace SH Wong, and ML Dennis Wong, “Battery-SC Hybrid ESS in Stand-alone DC Microgrids: A Review”, in IET Renewable Power Generation, vol. 11, no. 4, pp. 461-469, 2017.
Wenlong Jing, Chean Hung Lai, Wallace SH Wong, and ML Dennis Wong, “A Comprehensive Review of Energy Storage Technologies and Case Study for PV Residential Energy Storage Applications”, (submitted to Journal of Energy Storage on Sept 2018)
Wenlong Jing, Chean Hung Lai, Derrick K.X. Ling, Wallace SH Wong, and ML Dennis Wong, “Battery Lifetime Enhancement via Smart Hybrid Energy Storage Plug-in Module in Stand-alone Photovoltaic Power System”, Journal of Energy Storage, Volume 21, February 2019, Pages 586-598.
Conference Papers
Wenlong Jing, Derrick K.X. Ling, Chean Hung Lai, Wallace SH Wong, and ML Dennis Wong, “Hybrid Energy Storage Retrofit for Stand-alone Photovoltaic-Battery Residential Energy System”, The 7th Innovative Smart-grid Technologies (ISGT Asia 2017), Auckland, New Zealand, December 4 – 7, 2017.
Wenlong Jing, Chean Hung Lai, Wallace Wong Shung Hui, M.L. Dennis Wong, “Cost Analysis of Battery-SC Hybrid ESS for Stand-alone PV Systems”, 4th IET International Conference on Clean Energy and Technology, November 2016.
Wenlong Jing, Chean Hung Lai, Wallace SH Wong, and ML Dennis Wong, “Theoretical Analysis and Software Modeling of Composite Energy Storage Based on Battery and SC in Microgrid Photovoltaic Power System”, (ICISCA-2015) International Conference on Information, System and Convergence Applications, Kuala Lumpur, 2015.
Wenlong Jing, Chean Hung Lai, Wallace SH Wong, and ML Dennis Wong, “Smart Hybrid Energy Storage for Stand-alone PV Microgrid: Optimization of battery lifespan through dynamic power allocation”, IEEE PES Asia-Pacific Power and Energy Engineering Conference, pp. 1-5, Brisbane, 2015.
Wenlong Jing, Chean Hung Lai, Wallace SH Wong, and ML Dennis Wong, “The Comparison between Two Types of Bidirectional Dual Active Bridge DC/DC Converter for Photovoltaic Application”, (In progress)
I
Table of Contents
List of Figures .............................................................................................................................. V
List of Tables ................................................................................................................................ X
Nomenclature .............................................................................................................................. XI
Chapter 1 Introduction ........................................................................................................... - 1 -
1.1 Research background ................................................................................................ - 1 -
1.2 Problem statement ..................................................................................................... - 3 -
1.3 Research contributions .............................................................................................. - 4 -
1.4 Outline of the thesis................................................................................................... - 5 -
Chapter 2 Review of Energy Storage Technologies .............................................................. - 8 -
2.1 Introduction ............................................................................................................... - 8 -
2.2 Modern power system with energy storage ............................................................... - 8 -
2.3 Energy storage technologies .................................................................................... - 13 -
2.3.1 Mechanical energy storage .................................................................................. - 13 -
2.3.2 Electrical energy storage ..................................................................................... - 18 -
2.3.3 Electrochemical battery ....................................................................................... - 20 -
2.3.4 Thermal energy storage (TES) ............................................................................ - 27 -
2.3.5 Chemical energy storage ..................................................................................... - 28 -
2.4 ESS characteristics .................................................................................................. - 30 -
2.4.1 Technical characteristics comparison of energy storage technologies ................ - 30 -
2.4.2 Summary table of energy storage characteristics ................................................ - 37 -
Table of Contents
II
2.4.3 The selection of energy storage technologies ...................................................... - 38 -
2.5 General discussion on energy storage technology and future development ............ - 41 -
2.6 Conclusion ............................................................................................................... - 45 -
Chapter 3 Solar PV Technology and Energy Storage in Stand-alone Power System .......... - 47 -
3.1 Introduction ............................................................................................................. - 47 -
3.2 Overview of solar PV technology ........................................................................... - 48 -
3.2.1 Background of solar cell ..................................................................................... - 48 -
3.2.2 Solar cell model ................................................................................................... - 49 -
3.2.3 Overview of the PV power system ...................................................................... - 52 -
3.3 Stand-alone PV power system ................................................................................. - 54 -
3.3.1 Components and system structure ....................................................................... - 54 -
3.3.2 Solar power generation ........................................................................................ - 55 -
3.3.3 Load demand estimation ..................................................................................... - 56 -
3.4 Energy storage in stand-alone PV power system .................................................... - 58 -
3.4.1 Discussion about the selection of ESS ................................................................ - 58 -
3.4.2 Lead-acid battery and its stress factors ................................................................ - 60 -
3.5 Case study of stand-alone PV-Battery power system.............................................. - 61 -
3.5.1 Scaled prototype of stand-alone PV power system ............................................. - 63 -
3.5.2 The concept of SC/Lead-acid battery HESS ....................................................... - 64 -
3.6 Conclusion ............................................................................................................... - 65 -
Chapter 4 Study on Battery-SC HESS: Topology, Control Strategy, and Application ....... - 66 -
4.1 Introduction ............................................................................................................. - 66 -
4.2 Battery-SC HESS topologies .................................................................................. - 67 -
4.2.1 Passive Battery-SC HESS ................................................................................... - 68 -
4.2.2 Semi-Active Battery-SC HESS ........................................................................... - 69 -
4.2.3 Full Active Battery-SC HESS ............................................................................. - 70 -
4.2.4 Multi-level Battery-SC HESS ............................................................................. - 71 -
4.3 Energy management system (EMS) ........................................................................ - 72 -
Table of Contents
III
4.3.1 Overview of EMS ................................................................................................ - 72 -
4.3.2 The design considerations of EMS ...................................................................... - 74 -
4.3.3 Advanced algorithm in EMS ............................................................................... - 77 -
4.4 Analysis and discussion .......................................................................................... - 81 -
4.4.1 HESS topologies and EMS ................................................................................. - 82 -
4.4.2 Summary of the advantages of Battery-SC HESS .............................................. - 83 -
4.4.3 AC coupled and hybrid AC/DC PV-HESS power system .................................. - 84 -
4.4.4 HESS topologies and EMS in rural electrification .............................................. - 85 -
4.5 Conclusion ............................................................................................................... - 85 -
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification ... - 86 -
5.1 Introduction ............................................................................................................. - 86 -
5.2 Selected HESSs for stand-alone PV power system in rural electrification ............. - 87 -
5.3 Stand-alone PV power system with selected HESSs .............................................. - 88 -
5.3.1 With Passive HESS ............................................................................................. - 88 -
5.3.2 With SC Semi-Active HESS ............................................................................... - 93 -
5.3.3 SC/Lithium-ion/Lead-acid battery Multi-level HESS ......................................... - 97 -
5.4 Numerical simulations in stand-alone PV power system ...................................... - 102 -
5.4.1 Solar irradiance and load profiles for case studies ............................................ - 102 -
5.4.2 Results of simulations ....................................................................................... - 104 -
5.4.3 Battery health assessment and financial analysis .............................................. - 111 -
5.5 Experiment verification ......................................................................................... - 119 -
5.5.1 Testbed setup ..................................................................................................... - 119 -
5.5.2 Pulse load response ........................................................................................... - 120 -
5.5.3 Daily operation in stand-alone PV power system ............................................. - 122 -
5.6 Conclusion ............................................................................................................. - 124 -
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System ......... - 125 -
6.1 Introduction ........................................................................................................... - 125 -
6.2 SHESS Plug-in module ......................................................................................... - 127 -
Table of Contents
IV
6.2.1 System structure ................................................................................................ - 127 -
6.2.2 Power allocation and control strategy ............................................................... - 129 -
6.3 Simulation analysis ............................................................................................... - 131 -
6.3.1 Pulse load response ........................................................................................... - 131 -
6.3.2 Operation in stand-alone PV-battery power system .......................................... - 134 -
6.4 Experiment verification ......................................................................................... - 140 -
6.4.1 Pulse load response ........................................................................................... - 141 -
6.4.2 Operation in the lab-scale stand-alone PV-battery power system ..................... - 143 -
6.5 Conclusion ............................................................................................................. - 148 -
Chapter 7 Conclusion and Future Work ............................................................................ - 149 -
7.1 Summary ............................................................................................................... - 149 -
7.2 Future work ........................................................................................................... - 151 -
Reference ............................................................................................................................... - 154 -
Appendix ............................................................................................................................... - 172 -
A.1. Case study ............................................................................................................. - 172 -
A.1.1 Existing power generation and distribution system in BANP ....................... - 172 -
A.1.2 Proposed solar-battery-generator hybrid power system ................................ - 174 -
A.2. Buck-boost DC/DC converter control and codes .................................................. - 178 -
A.2.1 The hardware structure .................................................................................. - 178 -
A.2.2 Control code in Arduino microprocessor ...................................................... - 179 -
V
List of Figures
Fig. 1.1 Typical PV power generation and load profile in Sarawak, Malaysia ......................... - 2 -
Fig. 1.2 Content summary of the study in this thesis ................................................................ - 4 -
Fig. 2.1 Power system and energy storage applications ............................................................ - 9 -
Fig. 2.2 Load levelling and capacity firming in fluctuating load profile using ESS ............... - 10 -
Fig. 2.3 The detailed components of the power system .......................................................... - 12 -
Fig. 2.4 Energy storage technology classification ................................................................... - 13 -
Fig. 2.5 Pumped hydro storage (PHS) in renewable power system ........................................ - 14 -
Fig. 2.6 Three types of compressed air energy storage (CAES) ............................................. - 15 -
Fig. 2.7 Schematic layout of diabatic CAES system ............................................................... - 16 -
Fig. 2.8 Schematic layout of adiabatic CAES system ............................................................. - 16 -
Fig. 2.9 The flywheel ESS ...................................................................................................... - 17 -
Fig. 2.10 Simplified cross-section of SC cell .......................................................................... - 18 -
Fig. 2.11 The superconducting magnetic energy storage (SMES) .......................................... - 20 -
Fig. 2.12 General structure of electrochemical cell batteries .................................................. - 21 -
Fig. 2.13 Simplified layout of NaS cell/battery....................................................................... - 23 -
Fig. 2.14 Simplified layout of the metal-air battery ................................................................ - 25 -
Fig. 2.15 Simplified layout of flow battery ............................................................................. - 26 -
Fig. 2.16 Simple layout of thermal ESS .................................................................................. - 28 -
Fig. 2.17 Hydrogen fuel cells .................................................................................................. - 29 -
Fig. 2.18 Energy storage characteristics taxonomy ................................................................. - 30 -
Fig. 2.19 Comparison of energy density and power density ................................................... - 31 -
Fig. 2.20 Comparison of specific energy and specific power ................................................. - 32 -
Fig. 2.21 Comparison of energy rating and discharge time duration in power rating ............. - 33 -
Fig. 2.22 Comparison of storage duration and self-discharge rate .......................................... - 34 -
Fig. 2.23 Comparison of energy capital cost and maturity level ............................................. - 35 -
Fig. 2.24 Comparison of energy capital cost and M&O cost .................................................. - 36 -
Fig. 2.25 The framework of the energy storage technology selection .................................... - 40 -
List of Figures
VI
Fig. 3.1 Solar cell classification .............................................................................................. - 48 -
Fig. 3.2 The equivalent circuit of solar cell ............................................................................. - 49 -
Fig. 3.3 The I-V and P-V characteristics of the solar cell ....................................................... - 51 -
Fig. 3.4 V-I and P-V curves in different intensity ................................................................... - 51 -
Fig. 3.5 Solar cells, PV modules, PV panels and PV arrays ................................................... - 52 -
Fig. 3.6 The classification of PV power system ...................................................................... - 53 -
Fig. 3.7 A typical stand-alone PV-battery power system ........................................................ - 54 -
Fig. 3.8 The 7-day solar irradiance in Kuching, Sarawak, Malaysia ...................................... - 56 -
Fig. 3.9 Assessment of load profile for a non-electrified rural community ............................ - 57 -
Fig. 3.10 Estimated load profiles of the target rural site in Sarawak, Malaysia ...................... - 57 -
Fig. 3.11 Actual load profiles of the target rural site in Sarawak, Malaysia ........................... - 58 -
Fig. 3.12 Electrochemical reaction of the Lead-acid battery................................................... - 60 -
Fig. 3.13 The curves of the Lead-acid battery healthy and stress factors ............................... - 61 -
Fig. 3.14 Matlab Simulink model of stand-alone PV-Lead-acid battery system .................... - 62 -
Fig. 3.15 Simulation current of stand-alone PV-battery power system (sunny) ..................... - 62 -
Fig. 3.16 Simulation current of stand-alone PV-battery power system (cloudy) .................... - 62 -
Fig. 3.17 Experimental current of stand-alone PV-battery power system (one day) .............. - 63 -
Fig. 3.18 Experimental testing of stand-alone PV-battery power system (2 hours) ................ - 64 -
Fig. 4.1 Classification of the battery-SC HESS topologies ..................................................... - 68 -
Fig. 4.2 Passive HESS topology.............................................................................................. - 68 -
Fig. 4.3 Semi-Active HESS topologies ................................................................................... - 69 -
Fig. 4.4 Active HESS topologies ............................................................................................ - 71 -
Fig. 4.5 Multi-level Battery-SC HESS topology ..................................................................... - 72 -
Fig. 4.6 The EMS with the multi-level control structure ........................................................ - 73 -
Fig. 4.7 Features and function of an efficient EMS design ..................................................... - 74 -
Fig. 4.8 Typical EMS for stand-alone PV power system with parallel active HESS .............. - 75 -
Fig. 4.9 Classification of intelligent algorithms for EMS supervisory control ....................... - 78 -
Fig. 4.10 Fuzzy logic flowchart .............................................................................................. - 79 -
Fig. 4.11 Genetic algorithm flowchart .................................................................................... - 80 -
Fig. 4.12 Dynamic programming flowchart ............................................................................ - 81 -
Fig. 4.13 The stand-alone PV-HESS power system expansion............................................... - 84 -
Fig. 5.1 Classification of the Battery-SC HESS topologies .................................................... - 87 -
Fig. 5.2 Multi-level HESS topology ........................................................................................ - 88 -
Fig. 5.3 The equivalent circuit of the Passive HESS ............................................................... - 89 -
Fig. 5.4 Matlab Simulink model of Passive HESS.................................................................. - 92 -
Fig. 5.5 Pulse load response of Passive HESS ........................................................................ - 92 -
List of Figures
VII
Fig. 5.6 Stand-alone PV power system with Passive HESS ................................................... - 93 -
Fig. 5.7 The equivalent circuit of the SC Semi-Active HESS................................................. - 93 -
Fig. 5.8 The Matlab Simulink model of the SC Semi-Active HESS ...................................... - 95 -
Fig. 5.9 Pulse load response of the SC Semi-Active HESS .................................................... - 95 -
Fig. 5.10 The stand-alone PV power system with SC Semi-Active HESS ............................. - 96 -
Fig. 5.11 Power allocation strategy for the SC Semi-Active HESS ........................................ - 97 -
Fig. 5.12 The equivalent circuit model of the Multi-level HESS ............................................ - 97 -
Fig. 5.13 The Matlab Simulink model of the Multi-level active HESS .................................. - 99 -
Fig. 5.14 Pulse load response of the Multi-level active HESS .............................................. - 100 -
Fig. 5.15 Stand-alone PV power system with Multi-level HESS.......................................... - 101 -
Fig. 5.16 Power allocation strategy for the Multi-level HESS ............................................. - 101 -
Fig. 5.17 The PV output in sunny day ................................................................................... - 102 -
Fig. 5.18 The PV output in cloudy day ................................................................................. - 103 -
Fig. 5.19 Estimated load profiles of the target rural site in Sarawak, Malaysia .................... - 103 -
Fig. 5.20 Matlab Simulink model of Passive HESS .............................................................. - 104 -
Fig. 5.21 Current profiles of sunny day ................................................................................ - 105 -
Fig. 5.22 Current profiles of cloudy day ............................................................................... - 105 -
Fig. 5.23 Matlab Simulink model of SC Semi-Active HESS ............................................... - 106 -
Fig. 5.24 Current profiles of sunny day ................................................................................ - 107 -
Fig. 5.25 Current profiles of cloudy day ............................................................................... - 107 -
Fig. 5.26 Matlab Simulink model of Multi-level HESS ........................................................ - 108 -
Fig. 5.27 Current profiles of sunny day ................................................................................ - 109 -
Fig. 5.28 Current profiles of cloudy day ............................................................................... - 109 -
Fig. 5.29 SoC variation of SC in three different scenarios (sunny day) ................................ - 110 -
Fig. 5.30 SoC variation of SC in three different scenarios (cloud day) ................................ - 110 -
Fig. 5.31 The results of the charge/discharge rate (sunny day) ............................................. - 113 -
Fig. 5.32 The results of the dynamicity (sunny day) ............................................................. - 113 -
Fig. 5.33 The results of the SoC (sunny day) ........................................................................ - 114 -
Fig. 5.34 The results of the charge/discharge transition (sunny day) .................................... - 114 -
Fig. 5.35 Normalized results of cost function throughout the sunny day .............................. - 115 -
Fig. 5.36 The results of the charge/discharge rate (cloudy day) ........................................... - 115 -
Fig. 5.37 The results of the dynamicity (cloudy day) ........................................................... - 116 -
Fig. 5.38 The results of the SOC (cloudy day) ...................................................................... - 116 -
Fig. 5.39 The results of the charge/discharge transition (cloudy day) .................................. - 117 -
Fig. 5.40 Normalized results of cost function throughout the cloudy day ............................ - 117 -
Fig. 5.41 Experiment setup of selected HESS topologies ..................................................... - 119 -
List of Figures
VIII
Fig. 5.42 Experimental responses to pulsed load of Passive HESS ...................................... - 120 -
Fig. 5.43 Experimental responses to pulsed loads of SC Semi-Active HESS ...................... - 121 -
Fig. 5.44 Experimental responses to pulsed loads of Multi-level HESS ............................... - 121 -
Fig. 5.45 Experimental currents of battery-only in stand-alone PV power system ............... - 122 -
Fig. 5.46 Experimental currents of Passive HESS in stand-alone PV power system............ - 123 -
Fig. 5.47 Experimental currents of Semi-Active HESS in stand-alone PV power system ... - 123 -
Fig. 5.48 Experimental currents of Multi-level HESS in stand-alone PV power system...... - 124 -
Fig. 6.1 The stand-alone PV power system with Lead-acid battery ...................................... - 125 -
Fig. 6.2 SHESS plug-in module in stand-alone PV-battery power system ........................... - 128 -
Fig. 6.3 Mode selection process of the proposed SHESS plug-in module ............................ - 129 -
Fig. 6.4 Power allocation strategy for the SHESS plug-in mode .......................................... - 130 -
Fig. 6.5 Matlab Simulink model of SHESS used in pulse load testing ................................. - 132 -
Fig. 6.6 Simulated results in pulse load testing in light mode ............................................... - 133 -
Fig. 6.7 Simulated results in pulse load testing in heavy mode ............................................ - 133 -
Fig. 6.8 Matlab Simulink model of stand-alone PV power system with SHESS .................. - 134 -
Fig. 6.9 Simulation results of plug-in testing in light mode .................................................. - 136 -
Fig. 6.10 Simulation results of plug-in testing in heavy mode .............................................. - 136 -
Fig. 6.11 Lead-acid battery currents profile in light mode .................................................... - 137 -
Fig. 6.12 Lead-acid battery currents profile in heavy mode.................................................. - 138 -
Fig. 6.13 Normalised cumulative battery health cost in light mode ...................................... - 139 -
Fig. 6.14 Normalised cumulative battery health cost in heavy mode ................................... - 139 -
Fig. 6.15 Prototype of the SHESS plug-in module ............................................................... - 140 -
Fig. 6.16 Experimental setup and circuit diagram for the pulse load testing ........................ - 142 -
Fig. 6.17 Experiment results of the pulse load testing (light mode)...................................... - 142 -
Fig. 6.18 Experiment results of the pulse load testing (heavy mode) ................................... - 143 -
Fig. 6.19 Experimental setup and circuit diagram for the case study.................................... - 144 -
Fig. 6.20 Experiment results of the stand-alone PV-battery power system .......................... - 144 -
Fig. 6.21 Experimental plug-in testing of SHESS plug-in module (light mode) .................. - 145 -
Fig. 6.22 Experimental plug-in testing of SHESS plug-in module (heavy mode) ................ - 146 -
Fig. 6.23 Experimental one day testing of SHESS plug-in module (light mode) ................. - 147 -
Fig. 6.24 Experimental one day testing of SHESS plug-in module (heavy mode) ............... - 147 -
Fig. A.1 Layout of BANP and current electricity supply system .......................................... - 172 -
Fig. A.2 Existing power consumption pattern of BANP ....................................................... - 173 -
Fig. A.3 Physical settings of the proposed system ................................................................ - 174 -
Fig. A.4 Connection diagram of the proposed system .......................................................... - 175 -
Fig. A.5 PV panels installation and research team ................................................................ - 176 -
List of Figures
IX
Fig. A.6 Control system installation (MPPT + OPTI-Solar Controller) ............................... - 176 -
Fig. A.7 Main switches installation (Load+PV+Battery+Controller) ................................... - 177 -
Fig. A.8 2400Ah PK200-12 Lead-acid battery bank Installation .......................................... - 177 -
Fig. A.9 Actual load profile collection .................................................................................. - 178 -
Fig. A.10 The system architecture diagram of DC/DC converter ......................................... - 178 -
Fig. A.11 The bidirectional buck-boost DC/DC converter ................................................... - 179 -
X
List of Tables
Table 2.1 Applications of energy storage in the power system ............................................... - 11 -
Table 2.2 Comparison of battery technologies ........................................................................ - 27 -
Table 2.3 Summary of energy storage characteristics ............................................................. - 37 -
Table 3.1 Three main types of solar cells in the market .......................................................... - 49 -
Table 5.1 Model parameters for different HESS under simulation ....................................... - 104 -
Table 5.2 Financial analysis under different modes .............................................................. - 118 -
Table 5.3 Experimental testbed parameters .......................................................................... - 120 -
Table 6.1 Comparison of energy storage technologies in SHESS ........................................ - 126 -
Table 6.2 Financial analysis of SHESS under different modes............................................. - 140 -
Table 6.3 Experiment testbed parameters ............................................................................. - 141 -
Table A.1 Electrical appliances (currently in-use) of main office and barrack A ................. - 173 -
Table A.2 Solar installation checklist ................................................................................... - 175 -
XI
Nomenclature
Abbreviations Description
ADC Analog to Digital Converter
BANP Batang Ai National Park Headquarter
C-Rate Charge and Discharge Rate
CAES Compressed Air Energy Storage
DoD Depth-of-Discharge
DAC Digital to Analog Converter
EMS Energy Management System
EMU Energy Management Unit
ESS Energy Storage System
FBC Filtration-Based Controller
FES Flywheel Energy Storage
GPMES Gravity Power Module Energy Storage
HVAC Heating, Ventilation, Air-Conditioning
HESS Hybrid Energy Storage System
IEA International Energy Agency
LA Lead-Acid
LCOE Levelized Cost Of Energy
Nomenclature
XII
LCOS Levelized Cost Of Storage
LCIA Life Cycle Impact Assessment
LPF Low-Pass Filter
MPP Maximum Power Point
MPPT Maximum Power Point Tracking
PV Photovoltaic
PSB Polysulphide Bromide
PAC Power Allocation Controller
PCU Power Conditioning Unit
PI Proportional-Integral
PWM Pulse Width Modulation
PHS Pumped Hydro Storage
RES Renewable Energy Sources
SHESS Smart Hybrid Energy Storage System
NaS Sodium-Sulphur Battery
SoC State-of-Charge
SC Supercapacitor
SMES Superconducting Magnetic Energy Storage
TES Thermal Energy Storage
VRB Vanadium Redox
VAR Voltage-Ampere Reactive
ZnBr Zinc Bromine
- 1 -
Chapter 1
Introduction
1.1 Research background
Modern electrical grid is required to provide reliable power supply that matches the
varying electricity demand from all sectors at all times. Aligning different sources of
power generation and varying load demand in an electricity network is one of the
biggest challenges for the utility company [1]–[3]. The unbalanced generation-demand
would potentially cause serious negative impacts on power quality such as voltage
variation, random frequency difference or sudden blackouts [4]–[7]. In addition, the
surplus electricity generated cannot be practically and economically stored which
requires it to be consumed at the instant when it is generated [8].
Ideally, energy storage system (ESS) as an intermediate buffer could potentially
alleviate some of the existing challenges such as frequency regulation, load levelling,
peak shaving and spinning reserve [9]. The key idea of energy storage integration is to
absorb excess energy when available, and to release the stored energy during peak
demand, which improves the flexibility and resilience of the electrical grid [10], [11].
There are numerous energy storage technologies available nowadays, which can be
broadly classified based on the form of energy stored: (1) mechanical (pumped hydro
storage, compressed air energy storage and flywheels), (2) electrical (supercapacitor and
superconducting magnetic energy storage), (3) electrochemical or battery (conventional
rechargeable batteries and flow batteries), thermal (latent heat storage and sensible heat
storage), (4) chemical (hydrogen fuel cells and thermochemical energy storage) and (5)
thermal energy storage (sensible heat storage and latent heat storage) [12].
Chapter 1 Introduction
- 2 -
ESS is also a vital tool for enabling integration of Renewable Energy System (RES) in
the electrical grid and distributed residential energy storage solution [13], [14]. Typical
renewable sources, such as solar, wind, biomass, geothermal, and tidal, are highly
intermittent in nature and often generate unstable and unpredictable electricity over time.
The undesirable fluctuating power generation from RES creates several issues such as
power safety, power quality, and reliability as well as islanding protection. Over recent
decades, solar photovoltaic (PV) technology has become one of the most prominent
RES due to many advantages such as modular, easy to install, mature technology and
most importantly low operating cost [15].
PV based power generation system can be categorized into grid-connected PV power
system and stand-alone PV power system. Low capacity stand-alone PV systems are
primarily used to supply electricity in off-grid communities such as remote rural areas,
to provide basic electricity needs for example lighting, food refrigeration and other
basic electrical appliances [16], [17]. Fig. 1.1 illustrates a typical profile of PV power
generation in tropical rainforest climate (red line) and the estimated load demand (blue
line) of rural communities. The nonlinear electrical characteristic of PV cells and
intermittency of solar irradiance require integration of intermediate ESS in order to
provide stable electricity supply, especially in stand-alone PV power system. ESS
absorbs the generation-demand mismatch and fluctuating power exchange in the system
through charge and discharge processes.
Fig. 1.1 Typical PV power generation and load profile in Sarawak, Malaysia
0 4 8 12 16 20 00
1
2
3
4
5
6
7
Pow
er (k
W)
Hours of Day
PV PowerLoad Profile
Chapter 1 Introduction
- 3 -
Lithium-ion and Lead-acid batteries are the two most commonly used energy storage
technologies in residential ESS [18]. The Lithium-ion battery has a higher energy
density, round-trip efficiency, and longer cycle lifetime compared to the Lead-acid
battery, but is relatively more expensive and immature in large-scale packaging. In
contrast, the Lead-acid battery is more suitable for off-grid PV power systems,
particularly in rural electrification due to its lower initial cost and excellent thermal
stability. Despite many advantages of integrating battery in stand-alone PV power
system, the highly dynamic fluctuations in generation and demand from the low-
capacity energy accelerate the battery aging process, which will significantly increase
the operating cost of the system [19], [20].
Hybridization of different energy storage technologies turns out to be one of the
promising solutions to mitigate the battery charge-discharge stress by directing the short
term power fluctuation to another form of energy storage such as the supercapacitor (SC)
[21]–[25]. Compared to electrochemical batteries, SC has very high power density, fast
response time and nearly infinite cycle life, which make it a good complement to the
Lead-acid battery bank in absorbing fluctuating power exchange [26]. Thus the concept
of Battery-SC Hybrid Energy Storage System (HESS) has been proposed by many
researchers aiming to mitigate the impact of fluctuating power on battery’s lifespan
[27]–[29]. In Battery-SC HESS, the net current flowing in and out of the HESS will be
divided into two or more components with varies frequencies. The SC absorbs the high
frequency and surge power exchange, while the battery bank responses to the smoothed
average power demand. The combination of battery and SC can provide a wide range
of power and energy requirements in stand-alone PV power systems. Besides having
correct combination and appropriate sizing of energy storage devices, the design of
Energy Management System (EMS) is another key to achieve better efficiency,
operation and maintenance costs reduction, and most importantly prolonged battery
service life [30]–[34].
1.2 Problem statement
In the perspective of rural electrification, the stand-alone PV power system is usually
installed to the places that are geographical dispersal, decentralized, low population
Chapter 1 Introduction
- 4 -
density and geographically isolated from the national grid, thus simple, stable and
inexpensive design of HESS will be of crucial useful than the high efficiency but a
costly and complex system [35]–[37]. Many research studies focused mainly on
proposing advanced and innovated HESS in aspects of novel topologies or complicated
EMS with hierarchical control, supervisory monitoring, adaptive droop moderate
scheme or control strategy based on the artificial intelligence algorithms [38]–[41].
These HESS designs are generally intended to serve large-scale utilities, smart-grid,
electric vehicles and other high power applications that require extensive sensing,
computation, and communication, this leads to increased system complexity and
implementation, and are not suitable in the rural area. However, the study on HESS for
off-grid residential energy system especially in rural electrification application is limited,
and their design considerations have not been systematically discussed. To address this
gap in the literature, this thesis conducted a study on the applications of HESS in stand-
alone PV power system for rural electrification.
1.3 Research contributions
The primary objective of this study is to enhance the service life of the Lead-acid
battery in stand-alone PV-battery power systems by mitigating life-limiting factors such
as current fluctuations and surge current. Thus, improving the system reliability and
power quality and most importantly reducing the system operating cost. To achieve this
aim, the research major works, methodology, contributions and outcomes are
summarised in Fig. 1.2 and as follows:
Fig. 1.2 Content summary of the study in this thesis
Major Work
• Battery-SC HESS study
• Lead-acid battery lifetime
enhancement in standalone PV
power system
Methodology
• Propose selection methodology
based on the overview of ESS
• Standalone PV power system
study and application of lead-
acid battery
• Discuss HESS topology and
select suitable topologies for
standalone PV Power system
• Propose Smart HESS as a plug-
in module
Contribution
• ESS selection methodology
• Load profile estimation
• HESS study for rural
applications
• Novel smart HESS plug-in
module is proposed
• Battery healthy assessment
system is proposed
Chapter 1 Introduction
- 5 -
Comprehensively review the existing energy storage technologies regarding
their technical merit, characteristic, economic feasibility and development trends.
Technical analysis, comparison and potential applications in modern power
system networks are presented. In particular, the methodology to help decision-
makers in identifying optimal energy storage technologies for specific
applications has been developed and discussed.
Investigate the lifetime characteristics of Lead-acid battery bank in power
system applications and identify the life-limiting factors that accelerate the
performance deterioration and aging process.
Investigate the effectiveness of hybrid ESSs in enhancing battery’s service and
feasibility in stand-alone PV-based power systems. This includes the
development status, operation principles, characteristics, advantages and
disadvantages, energy management and control strategies, and possible
application scenarios.
Complete the literature gap of the Battery-SC hybrid ESS in remote rural
applications.
Propose a novel smart hybrid ESS plug-in module that enhances the lifetime
characteristics of the primary Lead-acid battery in existing installed stand-alone
PV-battery power systems by mitigating life-limiting factors such as current
fluctuations and surge power demand.
Formulate a battery health cost function to quantitatively evaluate the negative
impact of charge/discharge current profile, follow with a series of battery health
cost analysis to systematically evaluate the effectiveness of different hybrid ESS
topologies and control schemes in mitigating battery stress, and perform
economic analysis and financial feasibility study.
Provide a complete analytical methodology for the research of the Battery-SC
HESS technology, including mathematical modelling, numerical simulation and
analysis, prototype design and corresponding experimental testing strategy.
1.4 Outline of the thesis
Chapter 2 presents an updated review of the currently available ESS technologies. The
following energy storage technologies, Pumped Hydro Storage (PHS), Compressed Air
Chapter 1 Introduction
- 6 -
Energy Storage (CAES), Flywheel Energy Storage (FES), Superconducting Magnetic
Energy Storage (SMES), Supercapacitor (SC), cell battery, flow battery, latent and
sensible Thermal Energy Storage (TES), hydrogen fuel cell energy storage and
thermochemical energy storage, will be present in terms of their operation, functionality,
distinct characteristics, limitations and advantages.
Chapter 3 introduces solar cell technology and PV power systems. A series of
considerations for the design of stand-alone PV power systems, such as solar irradiance
measurements, load profile estimation, and energy storage devices selection, are
discussed and presented. By using local solar irradiance and an estimated load profile, a
typical stand-alone PV-battery power system is modelled and simulated to show the
profiles of PV output power and battery currents. A lab-scale prototype of the stand-
alone PV-battery power system is constructed to show the performance experimentally.
Chapter 4 provides a study on the latest works related to Battery-SC HESS regarding
topologies, control algorithms and EMS, and the applications in PV based stand-alone
power system.
Chapter 5 discusses the potential Battery-SC HESS topologies that are suitable for the
stand-alone PV power systems in rural areas. Theoretical analysis and numerical
simulation in Matlab Simulink for the selected HESS topologies have been carried out,
and their effectiveness in mitigating battery stress are compared. The battery health cost
and financial analyses are presented to evaluate the life-extending capability of different
HESSs and their cost reduction in the overall system. The lab-scale prototypes of them
are developed, and their performances in stand-alone PV system are emulated to
validate the simulation analysis.
Chapter 6 proposes a smart SC/Lithium-ion HESS plug-in module that aims to extend
the Lead-acid battery lifetime in installed stand-alone PV-battery power systems
without reconstructing the system structure. It supposes to remove the severely current
fluctuations from the Lead-acid battery current profile and direct it passively operating
with a smoothing current profile. The proposed module is validated using numerical
simulation and prototype experiment.
Chapter 1 Introduction
- 7 -
Finally, in Chapter 7, the conclusion concludes this study with a summary and provides
suggestions for future research in this area.
- 8 -
Chapter 2
Review of Energy Storage Technologies
2.1 Introduction
Energy storage technologies store electrical, thermal, chemical and mechanical energy
and release them in the form of electricity when needed. Energy storage devices have
been widely used in various applications ranging from large-scale power systems to
distributed generation in microgrids, to improve the operational capability of power
systems, enhance power quality and reliability, and optimize power generation cost.
Besides, energy storage technology is also one of the vital components that enable the
adoption of RESs in the electrical power networks. Renewable energy sources, such as
solar, wind, biomass, geothermal and tidal, are often intermittent in nature that tends to
produce fluctuating and unstable electricity over time. The intermittent power
generation from RES creates issues such as power quality and reliability, power safety
and the needs for islanding protection. Energy storage technologies can be classified
into five major categories based on the form of energy when stored: (1) mechanical
energy, (2) electrical energy, (3) electrochemical energy, (4) thermal energy and (5)
chemical energy. The following sub-sections will present an overview of the modern
power system and a comprehensive review of energy storage technologies, including
their electrical and lifetime characteristics, technical analysis, and comparison.
2.2 Modern power system with energy storage
Fig. 2.1 shows a typical structure of modern power system consisting of subsystems
such as power generation, transmission, distribution, and end-users. The figure also
Chapter 2 Review of Energy Storage Technologies
- 9 -
summarizes the major challenges that exist in each subsystem, and the potential
applications of ESS across modern power system network [42]–[46].
Centralized Storage(>50MW)
ESS Substation(Up to 10MW)
Container ESS(Up to 2MW)
Residential(Up to 100 kW)
Industrial & Commercial
Generation Transmission Distribution
RES system
Load levelingFrequency regulation
Integration of RESVoltage SupportCapacity firming
Voltage regulationLoad shifting
Spinning ReserveNetwork stabilization
Upgrade power qualityCongestion relief
Micro-generation feed-in
End-users
Power Factor Optimize Time Shifting/ Peak Shaving
Stabilise PricesEmergency power back-up/ UPS
Applicationsummary
ESS sizereference
ESS Location
TransmissionSubstation
Step-upTransformer
Step-downTransformer
Residential
ESSLoad leveling• (~100MW, 4h)Frequency regulation• (1~50MW, 0.25~4h)
ESSIntegration of RES• (1~100MW, 1~10h)Voltage Support• (0.5~50 MVAr, 0.25~4h)
ESS
Spinning Reserve• (10~100MW, 0.25~10h)Load leveling for postponement of grid upgrade• (1~10MW, 6h)
ESSUpgrade power quality• (1~100MW, 0.25~6h)
ESS
Time ShiftUPS• (5~10 kW, 2~24h)
ESS
Peak Shaving• (5~10 MW, <1h)Power Factor Optimize Voltage Support• (0.5~50 MVAr, 0.25~4h)Emergency power back-up• (10~50 MW, 0.25~10h)
Fig. 2.1 Power system and energy storage applications
The primary role of the power system is to generate electricity that matches the
continually varying load demand as close as possible to avoid over-generation of
electricity and power deficit which requires load shedding remedy. Secondly, the power
system is required to maintain the system voltage and frequency at all times despite
random failure and/or variations at the generation side. ESS is one of the promising
solutions to enhance the reliability of the power system by acting as a contingency
reserve to provide immediate supply or spinning reserve during supply-demand
mismatch [47].
For load levelling application, ESS stores the excess energy at off-peak periods and
supply the stored energy during peak demand periods as shown in Fig.2.2 [48]. Besides,
the adoption of ESS can effectively counterbalance the power fluctuations from
generators to ensure frequency regulation [49]. The integration of ESS at generation
side can minimize the usage of costly load following power plant as well as wastage
during off-peak hours. In the case of renewable energy based generation, ESS plays an
important role to smooth (capacity firming) the intermittent RESs output power [50].
Chapter 2 Review of Energy Storage Technologies
- 10 -
Serious voltage collapse in power system due to excessive reactive power loss has been
one of the causes in major blackouts and voltage instability such as voltage sags,
voltage swells, frequency harmonics and flickers [51]–[53]. A stable electricity supply
requires a well-balanced real power and reactive power. The centralized power
generation supplies the real power and the reactive power can be generated either by
local Voltage-Ampere Reactive (VAR) supply or remote generators [54]. The local
VAR supply, also known as static compensation, can be the transformer tap changers,
switched capacitor banks and large rotating machines which are typically located within
the transmission and distribution sub-systems [55]–[57].
Fig. 2.2 Load levelling and capacity firming in fluctuating load profile using ESS
As an alternative technology, ESS can be used to effectively perform voltage regulation
and VAR support function [58]. Instead of the conventional methods where VAR (up to
10MW) is installed in transmission sub-system to control the voltage dynamic behaviors
and balance phase-angle difference between generation and demand sides, ESS
container (up to 2MW) can be installed at the end of distribution network that acts as an
energy buffer to provide stabilized high quality electricity to the loads [59].
In small-scale residential power applications, ESS can be used as a back-up power
supply or uninterrupted power supply. In addition, the ESS can be controlled to simulate
the time-shifting processes for which cheaper electricity at off-peak is stored and
provide electricity supply during peak hours [60]. Assuming well-coordinated time-
shifting processes at the demand side, the ESSs in distributed residential power system
networks not only reduce the electricity cost for the households, but the cumulative
Discharge energy storage
Smooth the peak power
Daily average load demand
Charge energy storage Load levellingUnstable
generationSupplement the
intermittent power
Chapter 2 Review of Energy Storage Technologies
- 11 -
effect of time-shifting could also be an attractive alternative to replace huge centralized
ESS at the generation side for load levelling.
With the rapid development of information technology and matured power electronic
technology, the traditional power system is undergoing a revolutionary transformation
in order to address the fast-growing global electricity demand, large-scale renewable
energy penetration, and large-scale multi-regional grid integration. The concept of
smart-grid has been widely accepted as one of the promising solutions for next-
generation power systems, for which the ESS is one of the critical components in the
modern power system network. Smart-grid incorporates the state-of-the-art technologies
in power electronics, sensors, control systems, communications and networking that
significantly improve the intelligence of the power system, including self-healing,
consumer-friendly, optimized asset utilization, eco-friendly, improved efficiency,
reliability, and safety [61].
Unlike the traditional power system, smart-grid allows seamless integration of
microgrids that contain distributed generations and loads. In general, sustainable energy
technologies such as solar PV, wind turbine and small hydro are often being integrated
into microgrids. Microgrid works as an independent small-scale, localized power system
that includes transmission, distribution, and EMS and energy storage [62]. Because of
the intermittency, variation and instability of renewable energy power generation, the
installation of ESS in the system will be essential to ensure power stability with
acceptable power balance, power quality, and reliability between power generations and
user demands.
Table 2.1 summarizes the applications of ESS in modern power system including
generation, transmission, power distribution, and demand side. In general, the
integration of ESS in the power system can effectively improve the electric grid
flexibility, resilience, technical efficiency and economic performance [42], [63]–[69].
Table 2.1 Applications of energy storage in the power system
Generation (Centralised and Distributed)
Transmission and Distribution
Load demand side
Chapter 2 Review of Energy Storage Technologies
- 12 -
Renewable energy integration Grid fluctuation suppression Capacity firming Ramping and Load Following Frequency regulation Seasonal energy storage Contingency reserve Black-start Spinning reserve Load Levelling / Peak Shaving
Voltage regulation Voltage-ampere reactive Transmission curtailment Transmission deferral Distribution deferral Transient stability Power quality Outage mitigation
Energy management Time shifting Demand side management Energy arbitrage Uninterrupted power supply Vehicle-to-grid Microgrid
The detailed components of the modern power system are summarized in Fig. 2.3 [70]–
[73]. The power system can be grid-connected or stand-alone or interchangeably with
advanced control strategy and switching. The power system contains energy sources,
interface components, power conversion system, control, and monitoring system, ESS
and loads. The power conversion system is the interconnection between systems of
different electrical characteristics, for example, the conversion from AC to DC or vice
versa. The loads include the end-use customer in different sectors which can be either
AC or DC.
Energy Source• Utility Grid• RES Microgrid• Hybrid Grid
Interface
Power Conversion System• Interconnection of AC/DC• AC/DC switchgear • Rectifier/inverter/converter• Control unit• Protection devices
(overvoltage, cooling, etc)
Loads• DC/AC• Industry• Residential
ESSs
Central Control System• Source/ESS/Interface/PCS/Load• Voltage/Frequency/VAR• Thermal management• Power conversion• Power dispatching• Protection devices • Subsystems control
Interface• Transmission Networks• HVDC/FACTS• Voltage transformers• Distribution Networks • Protection devices
Construction facilities• Electrical infrastructure• Telecommunication infrastructure• Lighting system• Grounding/cabling • Heating, ventilation, air-conditioning
(HVAC)
EMS
System Monitors • Sources/ESS/Interface/PCS/Load• Voltage/Frequency/VAR• Power flow • Power quality & Efficiency
Charge / discharge Power allocation SOC & Temperature Protection & SOH
Fig. 2.3 The detailed components of the power system
The power system with ESS integrated allows the surplus electricity to be stored in
energy storage devices and dispatched during high electricity demand for improved
efficiency. The ESS contains three main components that are charge/discharge module,
energy storage devices, and energy management system. The charge/discharge module
Chapter 2 Review of Energy Storage Technologies
- 13 -
manages the energy that flows in and out of the energy storage devices, while the EMS
monitors, controls and manages the ESS to ensure safe operation.
2.3 Energy storage technologies
Energy storage technology can be classified into five categories based on the form of
stored energy, which are (1) Mechanical, (2) Electrical, (3) Electrochemical, (4)
Thermal and (5) Chemical. Fig. 2.4 shows the classifications of energy storage
technologies available today. The following subsections present a comprehensive
review and discussion on each ESS, including their electrical and lifetime characteristics,
operating principles, system components, advantages as well as limitations.
Energy Storage Technologies
Mechanical Electrical Electro-chemical Thermal Chemical
Potential EnergyPumped Hydro Storage (PHS)
Compressed Air Energy Storage (CAES)
Kinetic EnergyFlywheel Energy Storage (FES)
ElectrostaticSupercapacitor (SC)
MagneticSuperconducting Magnetic Energy Storage (SMES)
Cell Batteryeg. Lead Acid / Sodium-Sulfur / Lithium-Ion / Nickel / Metal-Air
Flow Batteryeg. Vanadium Redox / Zinc Bromine / Cerium Zinc / Polysulfide Bromide
Latent ThermalSolid-Liquid
Liquid-Gaseous
(Phase Change)
Sensible ThermalLiquids-Liquids
Solids-Solids
(Non-phase Change)
Fuel Celleg. Proton exchange membrane / Phosphoric acid / Solid oxide / Molten carbonate
Thermochemicaleg. Ammoniates / Hydrate / Metal Hydrate
(Sorption Process)
eg. Hydration / Carbonation
(Chemical Reactions)
Fig. 2.4 Energy storage technology classification
2.3.1 Mechanical energy storage
Electrical energy can be converted and stored in the form of potential energy and kinetic
energy. Pumped hydro energy storage (PHS) and compressed air energy storage (CAES)
are two common potential ESSs. While flywheel technology converts and stores energy
in the form of rotational energy.
a. Pumped hydro storage (PHS)
Chapter 2 Review of Energy Storage Technologies
- 14 -
Low DemandCharging (Pumping up)
Lower ReservoirEnd-User
Pump/Turbine for Charging Motor/Generator for Discharging
Tunnels
Renewable Energy Generation
High DemandDischarging (Generation)
Higher Reservoir
Generator
Turbine
HeightGravitational potential energy ≈
Electricity
Fig. 2.5 Pumped hydro storage (PHS) in renewable power system
Fig. 2.5 shows the structure of PHS, where two reservoirs at different altitudes are used
to achieve electrical energy storage and conversion to gravitational potential energy [74].
PHS was first implemented in Switzerland and Italy in 1890 and currently accounts for
95% of global energy storage capacity [75], [76]. There are currently more than 300
PHS plants worldwide with a total installed capacity of 169 GW. The largest PHS plant
is rated at 3 GW and can last 10 hours at rated power [77]. Compared to other energy
storage technologies, PHS is considered as a large-scale energy storage and is
commonly used for daily load levelling and seasonal energy storage applications.
The storage capacity of PHS depends on the elevation difference between the two
reservoirs and the maximum amount of water that can be stored in the higher reservoir.
During off-peak hours, excess power is used to run electric pumps to transfer water
from the lower reservoir to the upper reservoir. During the high power demand period,
the stored water in the higher reservoir is released to run turbines to generate electricity.
The round-trip efficiency of PHS is reported to be between 70% and 85%, mainly due to
energy losses during pumping and generation processes. PHS is one of the most cost-
effective ways to store large amounts of energy. However, the implementation of PHS
is limited by high initial cost, complex geographic location requirements, long
construction periods, and potential negative ecological and environmental impacts [78].
Chapter 2 Review of Energy Storage Technologies
- 15 -
b. Compressed air energy storage (CAES)
Air Storage Vessel
Air Shaft
Water
Compressed air
Impermeable Caprock
Porous and Permeable LayerLower
Water Tank
WaterCompensation
tunnel
Upper Water Tank
Caverns in Hard Rock Formation
Typical CAES Hard-Rock Cavern CAES
Aquifer Reservoir CAES
(a) (b) (c)
Wells
Fig. 2.6 Three types of compressed air energy storage (CAES)
CAES technology is highly equivalent to PHS in terms of their operation principle,
application scenarios, input/output form, and storage capacity. But unlike PHS, which
moves water from lower reservoirs to higher reservoirs, CAES stores energy in the form
of compressed air and is usually stored in large underground caverns (aquifers, hard
rock caverns, underground natural gas storage, or salt caverns) with air pressure ranging
from 40 to 70 bars, as shown in Fig. 2.6 [79]–[81]. The excess power generated during
off-peak hours is used to compress air, which can be released to drive the gas turbine
generator to meet higher power demand during peak hours. CAES has high energy and
power density, which is considered as long-term energy storage technology. CAES has
been widely used in load shifting and power smoothing applications [82], [83].
However, similar to PHS, its development is mainly limited by geographical location
and large initial cost. There are two common types of CAES based on how heat is
handled during the compression and storage processes, namely diabatic CAES and
adiabatic CAES, as shown in Fig. 2.7 and Fig. 2.8 respectively [84].
Chapter 2 Review of Energy Storage Technologies
- 16 -
Fig. 2.7 Schematic layout of diabatic CAES system
M
Heat Storage
Compressed Air
G
Compressor Train
Air Inlet
Air Outlet
Power In
Power Out
Air Turbine
Fig. 2.8 Schematic layout of adiabatic CAES system
Heat will be generated during the compression process and dissipated during the
expansion process. The diabatic CAES removes heat produced in the compression with
intercoolers. A reheating process with a gas-fired burner is often needed before
expansion in the turbines, which decreases the round-trip efficiency to about 40% to 50%
[85]. If the heat generated during the compression process (charging process) can be
stored and used during the expansion process (discharge process), the round-trip
efficiency can be significantly improved. The adiabatic CAES storage retains the heat
during compression with well-insulated heat storage and returns the heat during
expansion process while running the turbine generators. The round-trip of adiabatic
CAES power plant has been reported to be approximately 70% [86]–[88].
Compressor train Expander/generator train
Fuel (e.g. natural gas, distillate)
IntercoolersHeat recuperator
PC PG
Air Exhaust
AirStorage
Aquifer,salt cavern,
or hard mine
hS = Hours ofStorage (at PC)
(power in) (power out)
Chapter 2 Review of Energy Storage Technologies
- 17 -
c. Flywheel energy storage (FES)
FES stores electrical energy in the form of kinetic energy by rotating mass, as shown in
Fig. 2.9. It comprises of a flywheel (steel or carbon composite) coupled with a high-
speed motor-generator and magnetic bearings that are mounted in a vacuum box in a
suspended state that aims to reduce self-discharge loss [89]. The stored energy is
calculated as E = Jω2/2, where ω is the angular velocity and J is the moment of inertia
[90]. The faster the flywheel rotates the more energy it stores. FES is considered as
short-term energy storage since the discharge time is from few mins to hours.
Fig. 2.9 The flywheel ESS
There are two types of FES based on the flywheel rotating speed: (1) low speed FES (up
to 6000 rpm), and (2) high speed FES (up to 60,000 rpm). The low-speed FES has a
specific energy close to 10-30 Wh/kg and they are made of steel rotors and conventional
bearings. High-speed FES can achieve a specific energy of 100 Wh/kg because of its
lightweight and high strength composite rotors. Low-speed FES is suitable for
applications that require short-term energy storage with high power capacity. On the
other hand, high-speed FES aims to serve applications that require medium-term energy
storage with a relatively lower power rating. During the charging process, the flywheel
is accelerated by a high-speed motor to convert the electrical energy to kinetic energy of
the rotating mass. When electrical energy is needed (discharging process), the rotating
flywheel is used to drive the generator in order to generate electricity. FES system
performs a series of good characteristics such as high power density, long cycle life (up
TopBearing
Motor/Generator
Rotor
BottomBearing
Shaft
Control
Chapter 2 Review of Energy Storage Technologies
- 18 -
to 100,000 cycles), high round-trip efficiency (80% to 90%), no Depth-Of-Discharge
(DoD) effect, wide operating temperature range, and environment-friendly.
FES technology is theoretically suitable for energy storage applications that experience
frequent charge-discharge cycle, require short to medium term energy storage and fast
response. For example, uninterrupted power supply, ancillary services, peak power
buffer, solar or wind power system and aerospace applications [90], [91]. The main
shortcomings of FES are the high energy cost (up to 1400 US$/kW) and high self-
discharge rate.
2.3.2 Electrical energy storage
Electrical ESS stores energy in the form of electrostatic or electromagnetic energy that
includes SCs and superconducting magnetic energy storage.
a. Supercapacitor (SC)
SC, also known as ultracapacitor or electrochemical double-layer capacitor, stores
electrical energy in the form of the static electric field. As shown in Fig. 2.10, SC
consists of metal plates, polarized electrode, electrolyte, and separator (ion-permeable
membrane) [26]. Due to the porous and large specific surface area, the highly activated
porous carbon is used as the polarized electrodes.
Fig. 2.10 Simplified cross-section of SC cell
The two electrodes are separated by the separator and electrically connected to each
other by the electrolyte. The separator serves as a physical separation between the two
electrodes, which provides insulation and allows ion conduction between the two
Current Collector
Positive Electrode
-- - - - -
++ + + + +Negative Electrode
Current Collector
Separator
Chapter 2 Review of Energy Storage Technologies
- 19 -
oppositely polarized electrodes. During the charging process, ions in the electrolyte
migrate to the opposite polarity of the electrode, and the electrostatic field are formed at
the interface between electrolyte and electrode on both sided of the separator that
creating an electric double layer. The double layer increases the surface area that allows
a relatively large amount of electrical energy to be stored and thus having a capacitance
that is thousands of times larger than a conventional electrolytic capacitor. Compared to
other energy storage technologies such as electrochemical batteries, SC has higher
power density ranging from 800-2000 W/kg. Similar to the conventional electrolytic
capacitor, SC has nearly infinite charge/discharge cycles without degradation, with an
efficiency as high as 95%.
Typical single SC cell operates in the low voltage range and can be connected in series
or in parallel to form modules and arrays to suit different application requirements. The
relatively higher self-discharge rate and low energy density of SC limit it to only short-
term applications. Short-term energy storage applications such as regenerative braking
in electric vehicles have become one of the main application areas of SC arrays, where
the SC array is designed to absorb and supply surge power demands during acceleration
and braking events. Research and development works for the next-generation SC have
been on-going and are mainly focusing on novel capacitive materials with larger
capacitance, such as graphene.
b. Superconducting magnetic energy storage (SMES)
The concept of SMES was first proposed by M. Ferrier in 1969 [92]. SMES stores
energy in superconducting magnetic conductors in the form of electromagnetic energy.
Fig. 2.11 shows a schematic of SMES with the superconducting coils as a core
component that placed in a helium vessel. The coils form a conductor that is made of
superconducting materials, such as Niobium-Titane (NbTi) wire operating at an
extremely low temperature (-270°C). The low-temperature environment allows the
superconducting materials to carry the electrical current as a large inductor and generate
a magnetic field with almost no resistive losses. The conductor inductance determines
the capacity of SMES and the corresponding maximum allowed current. The stored
energy in a typical SMES can be formulated as [93]:
Chapter 2 Review of Energy Storage Technologies
- 20 -
𝑊 = 1
2𝐿 ∙ 𝑖2 (2.1)
where W is the stored energy inside the superconducting magnet conductor, L is its
inductance, and i is the current flows in the coil. Under the superconducting state, the
current density inside the SMES is ten to hundred times higher than conventional coil
and therefore higher power density (up to 105 kW/kg), and energy density (1-10 Wh/kg)
can be achieved. SMES has a series of advantages such as high efficiency of 90-95%, a
large number of charge-discharge cycles, environmentally friendly, and fast response
during charge-discharge processes (less than 100 milliseconds).
Fig. 2.11 The superconducting magnetic energy storage (SMES)
The installed capacity of typical SMES is generally within 10 MW and are mainly used
for power quality improvement such as transient stability and spinning reserve in grid-
scale applications [94]. Moreover, SMES allows the stored energy to be fully
discharged, which is useful for applications that require continuously complete charge-
discharge operations. Currently, the SMES is still under development stage, and some
major shortcomings hinder the development, such as a complex structure in the
refrigeration system and control system, and most importantly the high cost in
superconducting materials.
2.3.3 Electrochemical battery
Electrochemical battery technology uses chemical reactions to exchange electrical
energy and chemical energy. There are two types of electrochemical storage system: (1)
cell battery and (2) flow battery.
a. Cell Battery
RefrigerationSystem
Controller
Load
Superconducting Coils
Helium Vessel
+
-
Chapter 2 Review of Energy Storage Technologies
- 21 -
Cell battery stores electrical energy in the electrode materials, while the flow battery
stores energy in the electrolyte. Fig. 2.12 illustrates the typical structure of the
electrochemical cell battery. Cell battery is a classical solution for storing electricity in
direct current form. It normally comprises of anode, cathode and the electrolyte that acts
as the medium allowing electrons exchange between two electrodes. It has the
rechargeable function of storing and releasing electricity via chemical reactions in
alternating the charge-discharge phases. Examples of cell battery technologies include
Lead-acid batteries, Lithium-ion batteries, sodium-sulphur batteries, nickel-based
batteries, and metal-air batteries.
Fig. 2.12 General structure of electrochemical cell batteries
LEAD-ACID BATTERY
The Lead-acid battery was first proposed in 1859 and is considered to be the oldest and
most matured cell battery technology. It composes of the lead-dioxide cathode, sponge
metallic lead anode and an electrolyte in sulphuric acid. The Lead-acid battery has an
energy density of up to 30 Wh/kg. As a rechargeable cell battery, it can tolerate
approximately 75% DoD and has approximately 1000-2000 cycles lifetime at 72-78%
efficiency. The Lead-acid battery has many advantages such as low cost, rapid
electrochemical reaction, simple power system installation, low maintenance, low self-
discharge rate (about 2-5% per month), and excellent thermal stability. Thus, the Lead-
Inverter/Converter
Load/Power system
ChargingDischarging
Electrolyte
+ -
Controller
Eg.Positive Electrode
PbSO4Li1-xMnO2
Metal (Mn, Co, Ni)…
Negative ElectrodePb
LixSiHydrogen-absorbing alloy
…
Chapter 2 Review of Energy Storage Technologies
- 22 -
acid battery is still one of the most widely used ESSs in various applications such as
uninterruptible power supplies, residential energy storage, backup power supplies,
automotive batteries, etc [95], [96]. Although the Lead-acid battery is the most matured
cell battery technology, the relatively short service life and poor lifetime characteristics
hinder its development in many application areas, such as power system and residential
energy storage [97], [98].
LITHIUM-ION BATTERY
The Lithium-ion battery has been widely used in consumer electronics (smartphones,
laptops, portable devices), and electric vehicles. It uses an intercalation lithium
compound as an electrode material, allowing lithium ions to move between electrodes
for charging and discharging processes. The advantages of Lithium-ion battery include
negligible memory effect, long lifetime (3000 cycles at 80% depth of discharge), high
power density (500-2000 W/kg), high energy density (80-190 Wh/kg), lightweight,
stable, low self-discharge rate (1–3% per month), abundant, high efficiency (90-100%),
and low cost cathode material [99], [100]. However, Lithium-ion batteries are more
expensive compared to other electrochemical energy storage devices, ranging from
$900/kWh to $1300/kWh. Other drawbacks such as sensitive to overcharge and deep-
discharge, for which additional State-of-Charge (SoC) monitoring and protection system
are required for safe operation [101]. The Lithium-ion battery is one of the most
promising energy storage solutions for the modern power system. However, the
weaknesses mentioned above must be addressed before it can be widely adopted in
large-scale energy storage applications as well as residential energy storage solution.
SODIUM-SULPHUR BATTERY (NAS)
The sodium-sulphur battery (NaS) was introduced in the 1960s and first commercially
available by the TEPCO (Tokyo Electric Power Co.) and NGK (NGK Insulators Ltd.) in
2000 [102]. NaS operates at a high temperature (300°C-350°C) and uses liquid sulphur
as the positive electrode and liquid molten sodium as the negative electrode, as depicted
in Fig. 2.13. The high temperature ensures the electrodes (Na and S) are in liquid state
with a high reactivity. The solid beta alumina ceramic electrolyte separates the two
electrodes. During charging process, the sulphur forming sodium polysulfide (Na2S4)
Chapter 2 Review of Energy Storage Technologies
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release the Na+ ions to the electrolyte and combine with elemental sodium, for which
electrical energy is converted to chemical energy, and vice versa during the discharging
process. The free electrons flow to the current collector that is connected to the external
circuit. During the operation, heat produced by the chemical reaction is sufficient to
maintain the required high operating temperature. The NaS battery has an energy
density of about 100 Wh/kg and allows 100% depth of discharge, performing 2,500
cycles at a high roundtrip efficiency of up to 89% [103]. High operating temperature
and highly corrosive sodium polysulfide in the electrode material limit the NaS
application to only large-scale energy storage solutions. NaS can be applied in the
transmission and distribution sections of the power system for power quality
improvement, transient stability, Transmission, and distribution deferral, and outage
mitigation [104]. Another major limitation of NaS is that it requires additional auxiliary
equipment to maintain the high operating temperature and to ensure safe operation.
Fig. 2.13 Simplified layout of NaS cell/battery
NICKEL-BASED BATTERY
The nickel-based battery uses the active material of nickel oxide hydroxide as the
positive electrode and varies metal elements as the cathode. Typical nickel-based
batteries include nickel-zinc (Ni-Zn), nickel-cadmium (Ni-Cd), nickel-metal hydride
(Ni-MH) and nickel-iron (NiFe). The Ni-Cd and Ni-MH batteries are relatively mature
Na+
BetaAluminaTube
SNa2S4
Sulfur
Volts
MoltenNa
Chapter 2 Review of Energy Storage Technologies
- 24 -
technologies and widely used in consumer electronics [105]. Ni-Cd battery use nickel
oxy-hydroxide and metallic cadmium as the electrodes. The energy density can reach up
to 75Wh/kg with a cycle life of approximately 2000-2500 [106]. The shortcomings are
the high self-discharge rate (5-20% per month) and the use of rare and highly toxic
electrode materials. Therefore, the Ni-Cd batteries have gradually lost their dominant
position in the consumer electronics market since the 1990s, and it was replaced by Ni-
MH and Lithium-ion batteries.
The Battle-Geneva Research Center around 1970 first invented the Ni-MH battery, that
uses metal hydride as the cathode [107]. Ni-MH battery has an energy density of up to
50 Wh/kg, the power density of up to 1000 W/kg and recorded 500 cycle life at 100%
depth of discharge. Compared to Ni-Cd battery of similar size, Ni–MH battery offers
30-40% more energy capacity and power capabilities, thus making it a more affordable
option for hybrid fuel-electric vehicles. Ni-MH batteries are widely used in hybrid fuel-
electric vehicles, contributing to over 95% of all market shares [108]. Other advantages
of Ni-MH include low maintenance, high power and high energy density,
environmentally friendly, safe operation during the charging-discharging transition at
high voltages.
METAL-AIR BATTERY
Metal-air battery uses pure metal as the anode and ambient air as the cathode from an
external system, its layout is shown in Fig. 2.14. The chemical reaction occurs in a tank
containing the aqueous electrolyte. Unlike the usage of aqueous in previous cell battery
technologies, the metal-air battery uses the ionic liquids as the electrolyte. Many metal
elements can be used as anodes, such as aluminum, calcium, barium, iron, lithium,
magnesium, potassium, silicon, sodium, tin, and zinc [109]. The most mature metal-air
batteries among them are the lithium–air and zinc-air batteries [110], [111], the latter is
more suitable due to cheap pure metal materials and low environmental impact. Metal-
air batteries are of interest to electric car companies because of their free cathode
materials and simple structures that do not require heavy enclosures to hold batteries
[112]. It can theoretically be designed to be ultra-lightweight and have a long-lasting
regenerative cathode, which is an attractive advantage in EV applications. For future
development, major limitations should be further considered, such as poor life cycle,
Chapter 2 Review of Energy Storage Technologies
- 25 -
low roundtrip efficiency of about 50%, unstable operating environment, and relative
safety issues [113], [114].
Fig. 2.14 Simplified layout of the metal-air battery
b. Flow battery
Flow battery, or redox flow battery, is a kind of electrochemical energy storage that
stores energy via two chemically electroactive materials. It converts electrical energy
into chemical potential energy by charging two liquid electrolytes and releasing stored
energy in reverse process. As shown in Fig. 2.15, the catholyte and anolyte are
externally stored in two separate electrolysis tanks/reservoirs, and the electrolyte is
pumped through the ion-exchange membrane cell. The reversible electrochemical redox
reaction occurs here and generates the electricity simultaneously. During charging, one
electrolyte is oxidized at the anode and the other electrolyte is reduced at the cathode.
The reverse process occurs during discharging. Flow battery has a roundtrip efficiency
of 70% to 85%. Since the battery capacity depends on the electrolyte volume and the
electrode surface area, the external electrolyte tank concept allows the battery to be
independently sized from different power or energy requirements in varies applications.
Moreover, it also results in that the flow battery can be recharged almost
instantaneously by recovering the spent electrolyte liquid for re-energization. In
addition, it has the advantages of low self-discharge percentage, fast response time,
tolerance to overcharge/over discharge, long lifetime (without phase transition during
Air : H2O, CO2, O2
Metal Anode
Temperature
Electrolyte Porous Carbon
Chapter 2 Review of Energy Storage Technologies
- 26 -
the process), low maintenance requirements and environment-friendly [115]. Currently,
the available flow batteries that has been developed over the past years contains
vanadium redox (VRB), polysulphide bromide (PSB), zinc bromine (ZnBr), and cerium
zinc (CeZn) [116]. They are generally considered to be an attractive technology for
relatively large scale energy storage applications in the 1 kW-10 MW range.
Fig. 2.15 Simplified layout of flow battery
c. Summary of electrochemical battery
Table 2.2 presents the technical comparison among these types of electrochemical
energy storage discussed above [73], [95], [101], [109], [117]–[120]. As a matured
energy storage technology and lowest cost per unit energy stored, the Lead-acid battery
is one of the preferred choices for small to medium scaled renewable and backup power
systems. Lithium-ion battery, with superior electrical characteristics, is currently
utilized in portable consumer electronic devices, the adoption in power system
applications are still low due to the safety issues and higher initial cost. On the other
hand, despite the excellent properties of NaS such as high energy density and small self-
discharge, the technology is still in the developmental stage due to the challenges in
maintaining the optimal operating temperature above 300°C. Unlike other
electrochemical batteries, the flow battery allows instant recharge by refilling the spent
Anolytereservoir
ElectrolyteA
Catholytereservoir
ElectrolyteB
Electrode
Ion-SelectiveMembrane
Flow Cell
LoadPump A Pump B
Chapter 2 Review of Energy Storage Technologies
- 27 -
electrolyte liquid. The flexible capacity, long service life, and low initial cost make the
flow battery an up-and-coming ESS technology in large-scale renewable power
generation plants.
Table 2.2 Comparison of battery technologies
Battery type Advantages Limitations
Lead-acid
Low costs Low self-discharge (2–5%per month) Low maintenance Most maturity technology
Short cycle life (1200–1800 cycles) Aging due to deep depth of charge Environment unfriendly (Pb & acid) Low power density
Lithium-ion
High efficiency 90–100% High energy density Low self-discharge rate Low maintenance No priming required Variety of types available
Overcharge protection is required Aging due to deep depth of charge Very high cost ($900–1300/kW h)
Nickel-based
Can be fully charged (3000 cycles) Higher energy density (50–
80 Wh/kg) Lowest cost/cycle Good low-temperature performance Available in a wide range of sizes
and performance options
High cost, 10 times of Lead-acid battery High self-discharge (10% per month) Sensitive to overcharge Memory effect Generates heat at high C-rate
Sodium Sulphur (NaS)
High efficiency 85–92% High energy density (90-120 Wh/kg) No degradation to deep charge No self-discharge Insensitivity to ambient conditions
Be heated in standby mode at 325 °C (Heating consumes 14% of battery energy per day)
High price in battery sealing to avoid leak
Metal-air High capacity low cost Removal of seal enables airflow
Sensitive to cold heat, humidity, and air pollution one-time use
Flow battery
Capacity can be modified via set tank size
Long service life (10,000 cycles) No degradation for deep charge Negligible self-discharge
Medium energy density (40–70 Wh/kg) High corrosion
2.3.4 Thermal energy storage (TES)
As shown in Fig. 2.16, TES technology stores energy via cooling or heating storage
medium materials in the insulated containers and the stored thermal energy can be used
directly in the domestic buildings, district heating, the industrial process needs where
consumes thermal energy, or in power generation applications via gas generator [121],
[122]. There are two types of TES technologies, latent heat storage and sensible heat
storage [123]. Latent TES uses the liquid-solid transition of phase change materials
Chapter 2 Review of Energy Storage Technologies
- 28 -
(PCMs) to exchange the thermal energy. During charging, the PCMs will shift from the
low internal energy state to higher internal energy state, such as solid to liquid and
liquid to gaseous. During retrieval, the higher internal energy state will transit back to
former state and release energy.
Fig. 2.16 Simple layout of thermal ESS
Unlike Latent TES, sensible TES stores the energy via high heat capacity of bulk
medium materials such as sodium, molten salt, pressurized water, etc. When the system
is charging, the bulk medium materials will be heated to a higher temperature. The heat
is then released to generate water vapour that drives turbo-generator system for
electricity. The main drawbacks include the low efficiency due to the energy losses
during heat process, weather sensitivity and require large volume or surface to get the
rated power.
2.3.5 Chemical energy storage
Chemical energy storage technologies include hydrogen fuel cells and thermal-chemical
energy storage. Hydrogen fuel cell as depicted in Fig. 2.17, comprises of electrolyze
unit, electrode storage tanks, and energy conversion cell. It uses the chemical reaction
between oxygen and hydrogen to generate electricity, the reaction results are water and
therefore offers zero-emission [124]. Up to 65% efficiency in hydrogen fuel cell has
been reported in the literatures [125]. Its benefits contain high energy density (300–
Heat Source
Heat Sink
Thermal energy storage (TES)
Charging Discharging
Heat Transfer Fluid
Pump
Chapter 2 Review of Energy Storage Technologies
- 29 -
1200 Wh/kg), low maintenance requirements, easy installation and environment friendly
with low toxic emissions. The main drawbacks of hydrogen fuel cells are the high cost
of hydrogen containers, stringent transport requirements, and the highly flammable
nature of hydrogen. Hydrogen fuel cell performs more than 20,000 lifecycles with about
15 years lifetime. Its initial cost mainly from the storage method ($2–15/kWh) and
storage equipment ($500–10,000/kW) [65][126][127]. While for the hydrogen
production, hydrogen production with costs in the range of 1.34~2.27 $/kg, using
available electrolysers [128][129]. Another form of chemical energy storage is the
thermos-chemical ESS. Similar to flow battery, thermos-chemical ESS has two separate
tanks to accommodate two different electrode materials. The heat energy is stored in the
endothermic chemical reaction in molecular level. The stored energy is used to break
the chemical bond (dissociation reaction) during the charging process, and then the
reverse reaction will release energy in the discharging process.
Fig. 2.17 Hydrogen fuel cells
Based on the type of reaction within the energy conservation cell, it can be classified
into sorption systems and pure chemical reaction system [130]. The thermos-chemical
energy storage has a relatively high energy density, which allows a large amount of
energy to be stored using small amounts of storage medium materials. The heat loss in
thermos-chemical energy storage is relatively low due to two separate storage tanks at
Oxygen
e-
Anode Cathode
Hydrogen
Chapter 2 Review of Energy Storage Technologies
- 30 -
ambient temperature. The technology is still under research and development stage,
with emphasis on reactor design, heat exchangers, and vacuum control.
2.4 ESS characteristics
A comprehensive understanding of ESS characteristics is essential in the consideration
and selection of suitable energy storage technologies for different application scenarios.
Fig. 2.18 presents the ESS characteristics in four different aspects, which are capacity,
efficiency, response, and product features.
ESS Characteristics
Capacity Efficiency
Power
Power Density (W/m3)
Specific Power Density (W/kg)
Energy
Efficiency
Round-trip Efficiency (%/cycle)
Discharge Efficiency (%)
Self-discharge (%/day)
Energy Density (Wh/m3)
Specific Energy Density (Wh/kg)
Response
Operation
Storage Duration
Discharge Time
Response time
Life
Calendar Life
Cycle Life
Product
Property
Memory Effect
Environmental Impact
Cost
Cost per unit Energy
Technology
Maturity
Applications
Fig. 2.18 Energy storage characteristics taxonomy
2.4.1 Technical characteristics comparison of energy storage technologies
a. Volumetric: power density and energy density
The volumetric property of ESS is an important factor in many applications, such as
power transmission, portable devices, automotive, and remote applications. For a given
energy capacity of ESS, the higher power and energy density is often desirable. Fig.
2.19 depicts the volumetric properties of different ESSs, with the nominal values of
1000W/L and 100Wh/L set for power density and energy density respectively. The
bottom left corner indicates the ESS with low energy density and power density, and
vice versa for ESS located at the top right corner.
Chapter 2 Review of Energy Storage Technologies
- 31 -
PHS and CAES are low in energy density and power density by nature, which are
normally implemented in large-scale and stationary energy storage project. In the top
left corner, the SC, SMES, and flywheel are having high power density but relatively
low in energy density. SC has the largest power density beyond 10,000 W/L, while its
energy density is in the range of 10-30 Wh/L. In general, SC, Flywheel, and SMES have
speedy response times, which are typically in the range of milliseconds. As one of the
oldest electrochemical battery, the Lead-acid battery has a relatively higher energy
density in the range of 50-90 Wh/L among the ESS grouped in the bottom left region.
Lithium-ion battery exhibits high power density and energy density among all energy
storage technologies. In the bottom right corner, the Zn–air battery as an emerging
energy storage technology has demonstrated superior energy density, making it one of
the promising energy storage solutions in power transmission systems.
Fig. 2.19 Comparison of energy density and power density
b. Gravimetric: specific power and specific energy
Specific energy and specific power are gravimetric characteristics that indicate the
energy or power per unit weight. Fig. 2.20 illustrates the technical comparison of
different ESS regarding specific power and specific energy. The VRB flow cell is
High100Low
1000
High
Energy Density (Wh/L)
Pow
er D
ensi
ty (W
/L)
Low
Lead-acid ZnBr VRB
Nickle-metal PHS CAES
SC SMES
Flywheel
NaS Fuel Cell
Zn-air
Li-ion
Chapter 2 Review of Energy Storage Technologies
- 32 -
located in the lower left area and performs the lowest specific power and specific energy,
160-170 W/kg and 10-30 Wh/kg, respectively. In the upper right corner, Lithium-ion
and Zn-air batteries are the lightest energy storage technologies. Compared to Lithium-
ion battery, the Zn-air battery has a relatively lower power density, which makes them
less suitable for consumer electronic devices. On the other hand, SC, SMES, and
Flywheel energy storages demonstrate the highest specific power but lower specific
energy due to the electrical characteristics and energy conversion mechanism. SMES
has the highest specific power of 500-2000 W/kg, while SC exhibits an exceptionally
high power density in the range of 40,000–120,000 kW/m3. Due to their fast response
time, they are broadly applied to power quality management systems. The flow batteries
of VRB, ZnBr and Lead-acid battery have moderate specific energy and specific power,
which are suitable for many medium-sized stationary residential energy storage
solutions. The TES and fuel cell show high specific energy but low specific power
(lower right area), that are usually used for large-scale ESS projects.
High30Low
500
High
Specific Energy (Wh/kg)
Spec
ific
Pow
er (W
/kg)
Low
TES Fuel Cell
NaS Nickle-metal
SC SMES
Flywheel
Li-ion
Zn-airLead-acid
VRB
ZnBr
Fig. 2.20 Comparison of specific energy and specific power
c. Capacity: power rating and energy rating
Chapter 2 Review of Energy Storage Technologies
- 33 -
The power rating indicates that the amount of power in kW can flow in or out of the
energy storage at any given moment. The energy rating, or energy storage capacity,
describes the amount of energy or electricity that energy storage can be stored and
measured in kWh.
Based on the individual application scenarios of each energy storage technologies, Fig.
2.21 presents a comparison in energy rating and nominal discharge time duration at the
power rating. The SC, SMES, and flywheel, with the highest power density and lowest
energy density, are at the bottom of the chart. Their discharge time at rated power is
generally in the range of minutes. The cell battery and flow battery are middle range
energy storage devices with energy rating ranges from 1kWh to 1MWh, and the
discharge time can reach 10 hours at the rated power. The PHS, CAES, NaS, VRB,
hydrogen fuel cell and TES are ordinarily large-scale energy storage technologies with a
capacity of more than 10 MWh, and their discharge time at rated power can up to days.
Fig. 2.21 Comparison of energy rating and discharge time duration in power rating
d. Efficiency: discharge efficiency and roundtrip efficiency
Discharge efficiency and round-trip efficiency are two of the standard performance
indicators for energy storage technology. The roundtrip efficiency, or cycle efficiency,
is a ratio of output energy to input energy in one complete charge-discharge process.
The discharge efficiency represents the ability to transmit stored energy in the case of
full discharge. Most of the energy storage technologies perform medium to high cycle
days
10 hrs
1 hr
min
PHS CAES NaSVRB Hydrogen TES
Lead-acid Li-ion NiCd NiMH ZnBr
Flywheel SCSMES
Discharge Time duration (at power rating)
> 10MWh
1k-10M Wh
0.1-1 kWh
Energy rating
Chapter 2 Review of Energy Storage Technologies
- 34 -
efficiency of above 70%, except for CAES, TES, metal-air battery and hydrogen fuel
cell that generally exhibit lower efficiency below 60%. Efficiency enhancement has
been one of the main focuses in ESS research, aiming to minimize system cost.
e. Self-discharge rate and storage duration
The self-discharge rate (%), or idling losses rate, is a measure of how fast one energy
storage unit will lose its stored energy without being connected to load. The
phenomenon of self-discharge in energy storage device is mainly caused by undesirable
internal mechanical or chemical effects such as energy dissipation via heat transfer
losses in TES, the chemical reaction in batteries, friction energy loss in the flywheel, air
leakage loss in CAES, etc. The storage duration refers the time period that ESS can
provide from full charge to zero. Fig. 2.22 presents a comparison chart based on self-
discharge rate and storage duration for ESSs. The SC, SMES, and flywheel have the
highest self-discharge rate, and their storage duration can only be maintained within
hours. Therefore, they are limited to short-term storage applications. Large-scale energy
storage devices such as PHS, CAES, NaS, hydrogen fuel cell, and VRB, and ZnBr flow
battery have low self-discharge rates, which is capable of keeping the stored energy for
months. While the TES and conventional cell batteries such as Lead-acid, Lithium-ion,
Nickel-based batteries exhibit intermediate self-discharge rate of 0.05-5%. They are
commonly used for medium storage applications such as RES distributed power
systems, electric vehicles, and consumer electronics.
Fig. 2.22 Comparison of storage duration and self-discharge rate
months
days
hrs
mins
PHS CAES NaSVRB ZnBr Hydrogen
Lead-acid Li-ionNiCd NiMH TES
Flywheel SCSMES
Storage Duration
<0.1
0.03-5
15 – 40
Self-Discharge (%/day)
Chapter 2 Review of Energy Storage Technologies
- 35 -
f. Calendar Life and Cycle Life
The lifespan of ESS can be expressed regarding calendar life or cycle life. The calendar
life of an ESS indicates the period before an ESS deteriorates to an unacceptable state.
Cycle life represents the number of full charge-discharge cycles before significant
performance degradation. The lifespan of energy storage is an essential factor that
determines the system operating cost. In general, non-chemical based energy storage
technologies including PHS, CAES, flywheel, SC, SMES, and TES typically have much
longer lifetime compared to chemical energy storage technologies such as cell batteries,
flow batteries, and hydrogen fuel cell, due to the chemical deterioration and corrosion
phenomenon.
g. Maturity and economic cost
The technical maturity, memory effect, financial cost and environmental impact of
energy storage products are also important evaluation factors for selecting suitable
energy storage in specific projects. The maturity of energy storage technology can be
classified into five levels which are (1) research and development (R&D), (2)
proven/commercializing, (3) mature/commercialized, and (4) very mature/fully
commercialized.
SMES Flywheel
SC
Hydrogen fuel cellZnBr
CAESVRB
Latent TES
NaSLi-ionZn-air
Sensible TES
PHSNiMHNiCd
Lead-acid
R&D Proven/Commercializing
Mature/Commercialized
Very Mature/Fully commercialized
80,000
10,000
2,000
10
Energy Capital Cost ($/kWh)
Fig. 2.23 Comparison of energy capital cost and maturity level
Chapter 2 Review of Energy Storage Technologies
- 36 -
Fig. 2.23 presents the technology maturity versus energy capital cost of the different
energy storage technologies [131]. The cost of energy storage includes the energy
capital cost (initial cost) and maintenance and operation (M&O) cost. The former one is
usually expressed in cost/per unit ($/kWh). Well-developed energy storage technologies,
such as PHS and Lead-acid battery are classified as very mature, with a history of more
than 100 years. The sensible TES, Lithium-ion, Zn-air and NaS battery are mature
technologies that have been commercialized on the market for decades. They are
technically developed and commercially available in the industry, but stability,
reliability, and cost competitiveness are still evolving and need further improvement.
CAES, VRB flow battery, flywheel, and latent TES are on the commercializing stage
with some significant improvement before commercialization. Hydrogen fuel cell,
SMES, and ZnBr flow battery are still in their early stage of development.
SMESFlywheel
SC
Hydrogen fuel cellPHS CAES Li-ionNickel-based, TES
Lead-acid Flow batteries NaS
5 40 60 90
Energy Capital Cost ($/kWh)
M&O Cost ($/KW-year)
80,000
10,000
2,000
10
Fig. 2.24 Comparison of energy capital cost and M&O cost
Fig. 2.24 shows the comparison of M&O cost versus energy capital cost of energy
storage technologies under consideration. The energy capital cost and M&O cost are the
crucial aspects to consider when selecting energy storage for any project to ensure long-
term financial sustainability. For example, the Lead-acid battery has a relatively low
energy capital cost, but it requires a relatively higher M&O cost, which makes it
inappropriate for the large-scale energy storage applications. More financial analyses of
Chapter 2 Review of Energy Storage Technologies
- 37 -
different energy storage technologies in various application scenarios such as internal
rate of return, tariff reduction, price arbitrage evaluation, are reported in [132]–[134].
h. Other characteristics: memory effect, aging mechanism, environment impact
Other non-quantifiable energy storage characteristics are critical aspects to consider
when selecting an energy storage device. The memory effect is a unique feature of
nickel-based rechargeable batteries. It is an effect where the battery loses its maximum
energy capacity when it is repeatedly not completely discharged before being recharged,
which seems that the battery remembers the latest smaller capacity. While the aging
mechanism refers to the process of performance deterioration due to the physical and
chemical changes during operation. In general, the aging mechanism is commonly
found in chemical-based batteries due to the corrosion, and in mechanical-based energy
storage due to physical wear and tear.
Environmental impact is another issue to be considered when choosing energy storage
products or design ESS. The PHS and CASE require large-scale infrastructure which
may disturb the local ecosystem. The flywheel, SMES, and hydrogen fuel cell are
considered to have the least impact on the environment because there is no apparent
toxic emission or waste by-product that causes pollution. Chemical-based energy
storage technologies are using potential hazardous toxifying materials such as lead,
cadmium, bromine, lithium, etc. Thus the recycling process of the aged chemical battery
becomes extremely important, and additional attention needs to be paid to before their
implementation.
2.4.2 Summary table of energy storage characteristics
Table 2.3 presents the summary of characteristics, parameters and product features for
each of the energy storage technologies [63], [65], [75], [135], [136]. Inside the table,
the item of Energy capital costs means the rough estimation about the cost of an ESS
project to a commercially operable status.
Table 2.3 Summary of energy storage characteristics
ESS Technology
Power Density [W/L]
Specific Power [W/kg]
Self-discharge [%/day]
Discharge time
Cycle time (Cycles)
Energy capital costs ($/kWh)
Application
Scale
Chapter 2 Review of Energy Storage Technologies
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Energy Density [Wh/L]
Specific Energy [Wh/kg]
Round-trip efficiency [%]
Response time
Lifetime (Years)
Environment impact Maturity
Mechanical
CAES 0.5~2 Not appl. Small
hours~ days 8000~12000 2-50 Very large
2~6 30~60 40~50 s-min 20~40 Medium Proven
PHS 0.5~1.5 Not appl. Very small hours–
days 10000~30000 10~12 Very large
0.5~2 0.5~1.5 70~85 s-mins 30+ High Very Mature
FES 1000~5000 400~1600 20~100 mins~
hours 20000+ 1000~14000 Medium
20~80 5~130 85~95 10-20 ms 15~20 Very low Proven
Electrical
SC 40000~1200
00 500~15000 20~40 mins~ hours 100000+ 300~2000 Small/
Medium 10~30 0.1~15 85~98 10-20 ms 5~20 Very low Mature
SMES 1000~2500 500~2000 10~15 mins~
hours 100000+ 1000~72000 Large/Medium
2~6 0.5~5 >95 <100 ms 5~20 Low R&D
Battery
Lead-acid
10~400 75~300 0.1~0.3 hours 500~1000 200~400 Small/ Medium
50~90 30~50 80~90 ms 3~10 High Very Mature
Lithium-ion
1500~10000 230~340 0.1~0.3 hours 1000-20000 900~1300 Small/ Medium
150~500 100~250 90~98 10-20 ms 5~15 High/Medium Mature
NiCd 80~600 150~300 0.2~0.6 hours 2000~3500 500–1500
Small/ Medium
<200 45~80 70~75 ms 10~20 High Very Mature
NiMH 500~3000 70~800 0.4~1.2 hours 300~3000 270~530 Small
<350 60~120 70~75 ms 5~10 High Very Mature
NaS 120~180 90~230 ~20 hours 2000~4500 300~500 Large/Me
dium <400 150~240 85~90 10-20 ms 12~20 Medium/Low Mature
VRB 0.5~2 Not appl. 0~10 hours 12000+ 600–1500 Large/Me
dium 20~35 10~30 75~82 ms 10~20 Medium/Low Proven
ZnBr ~25 50~150 Small hours 2000+ 700~2500 Large
30~65 30~80 60~70 ms 5~20 Medium R&D
Zn-air 50~100 ~1350 Not appl. hours 2000+ 10~1000 Small
~800 ~400 60 ms 30+ Very low Mature
Thermal
Latent Heat
Not appl. 10~30 0.5~1 Not appl. Not appl. 3~80 Large/Medium
25~120 150~250 75~90 Not appl. 20~40 Low Proven Sensible Heat
Not appl. Not appl. 0.5 Not appl. Not appl. 0.04~50 Medium 100~370 10~120 70~90 Not appl. 10~20 Low Mature
Chemical
Hydrogen
Fuel-cell
>500 >500 0.5~2 hours-days 1000+ 500~3000 Large/Medium
500~3000 800~10000 30~50 s-mins 5~15 Very low R&D
2.4.3 The selection of energy storage technologies
In power system, the application of ESS can be divided into five categories: large-scale
energy services, transmission, and distribution infrastructure services, auxiliary services,
Chapter 2 Review of Energy Storage Technologies
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and residential energy storage solutions. The auxiliary service contains emergency
power back-up, peak shaving, time shifting and etc. Since each type of energy storage
technology has its unique characteristics, it is essential to select the optimal energy
storage technology for specific applications [137]–[139]. In general, the characteristics
that can be used to assess the applicability of energy storage technology for specific
applications include:
Energy rating and power rating; Energy density and power density; Response time; Self-discharge rate; Cycle efficiency; Rated voltage and current; Charge/discharge duration and ampere-hour; Operating temperature; Service life; Environmental impact; Cost, weight, and size.
The above characteristics can be sorted into three main categories: technical, economic
performance and environmental standards. In most cases, the rated power and duration
of discharge are the critical characteristics in selecting appropriate energy storage
technology for various applicationsm; this is mainly because that the functionality is a
prerequisite and to meet the technical requirements of the targeted system is the priority.
At the same time, ESS economic performance and environmental standards are also
important factors that influence the final decision. A typical method of analyzing the
economic performance of an ESS is the Levelized Cost Of Energy (LCOE), sometimes
referred to as Levelized Cost Of Storage (LCOS) [140]–[142].
The environmental standards mainly include the impact on the environment and the life
of the ESS itself. The Life Cycle Impact Assessment (LCIA) is a systematic and
commonly used method to assess the environmental impact of a product or process
system throughout its life cycle [143], [144]. With the various characteristics, no single
energy storage technology can fulfill all desirable requirements in different energy
storage applications. For example, the Lithium-ion battery is one of the best options for
small-scale portable devices because of its high power density, high energy density,
Chapter 2 Review of Energy Storage Technologies
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high efficiency, and reasonable cycle life. However, the higher initial cost and thermal
instability hinder its usage in residential energy storage applications. As an alternative,
the Lead-acid battery is a mature technology with relatively low cost and superior
electrical stability. It is a practical option for residential energy storage solution,
especially in stand-alone power systems. At the same time, however, in large-scale
situations (several kWh), the Lead-acid battery is not suitable because of its high M&O
cost and inefficiency.
Fig. 2.25 The framework of the energy storage technology selection
With the growth in ESS applications and options of energy storage technologies, it is
efficient for decision-makers to provide a framework that can facilitate the selection of
suitable ESSs. Fig. 2.25 shows the typical framework of the energy storage selection.
Technical, economic performance and environmental standards are evaluated using sub-
items that need to be balanced by decision-makers. The selection aims at finding the
most suitable energy storage technology that can not only meet the technical constraints
imposed by the target applications but also has the best overall performance in the main
criteria, for example, the one with high technology maturity, low total cost, and small
environmental impact.
Target ESS
Technical
Required installation
Duration
Maturity
Complexity
Economic performance
Initial cost (Budget)
Maintenance
Environmental standard
Lifecycles
Waste treatment
Environmental friendliness
Main-criteria Sub-criteria
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The main criteria in the three domains for selection normally include qualitative and
quantitative features. The quantitative considerations include efficiency, lifetime, cost,
power and energy densities, electrical response time, etc. A comprehensive quantitative
assessment can eliminate the effects of human factors and make the selection more
realistic. The qualitative considerations include the evaluation of energy storage
technologies attributes such as device properties, technology maturity, reliability and
safety, environmental impact, etc. Qualitative analysis will mainly base on the user
features, expert experience, and government policies to meet the environmental
requirements, cost requirements, and stability requirements for specific projects. Once
the appropriate energy storage product has been determined, the design of ESS will
follow the procedures:
1. Determination of the required size of the energy storage, such as voltage and
storage duration requirements (large, medium or small);
2. Determination of the energy storage structure that is required to meet the total
ampere-hour capacity (single, parallel or series);
3. Design the control system;
4. Design of construction facility at the installed site, including protection system,
monitoring system, cabling and etc.
The above procedures are the main steps in most ESS design process, and the detailed
design and installation steps will be sequentially expanded according to the different
application scenarios. As a case study to illustrate how to select and design an ESS in a
specific application, a stand-alone PV power system with energy storage will be
discussed in the next chapter.
2.5 General discussion on energy storage technology and future development
The design of energy storage technology normally involves multiple forms of energy,
multiple devices, multiple substances, and multiple processes. Over the past few
decades, researchers and industrial practitioners are putting great efforts in developing
advanced energy storage technologies to reduce economic costs while ensuring
longevity, good load regulation performance, high efficiency, and long-term reliability.
Chapter 2 Review of Energy Storage Technologies
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The ESS plays a crucial role in many aspects, including electric power transmission,
large-scale renewable energy based power plant, large-scale grid flexible
interconnection, residential RES based microgrid, and one of the necessary support
technologies for the smart-grid. The main applications of various types of energy
storage technologies are as follows:
1. Large-scale, long-term energy storage facilities, such as PHS and CAES, can be
used for large-scale power grid peaking shaving and seasonal storage. The flow
battery and thermal storage with the second large energy storage capacity, a large
number of cycles, and long service life can be used as load levelling devices in the
grid. While Hydrogen storage can be used to store surplus wind and solar energy
to power fuel cell vehicles.
2. The SC, SMES, flywheel energy storage, sodium-sulfur batteries, and other high
power density ESS are mainly operated in combination with large-scale RESs.
They can quickly respond to surge power generation and stabilize the fluctuations
from the RESs.
3. Lithium-based batteries, Lead-acid batteries, metal-air batteries, and other battery
ESSs are less suitable for large-scale power plants and are mainly used for
distributed residential energy storage applications and electric vehicles.
With the continuous innovation and development of new energy storage materials, it is
expected to make significant breakthroughs in extending service life, increasing energy
density, fast charging time, and reducing costs. Meanwhile, the deployment of ESS in
large-scale power grids and/or microgrids is still facing significant challenges, and they
shape the direction of research and development roadmap of energy storage technology,
which contains three key areas:
1. To enhance energy storage performance and reliability, effective supply chain and
fabrication processes to enable mass production, thus overall cost reduction;
2. Energy storage technology selection and performance optimization complementary
technologies for specific applications;
3. Formalization of a systematic approach in evaluating energy storage technologies
for different applications.
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For traditional large-scale energy storage technologies, PHS, CAES, and TES, their
main challenges are low roundtrip efficiency and higher implementation costs. The
refinements of the PHS system are mainly focusing on upscaling the hydroelectric
turbo-machinery, optimizing the operation efficiency via installing enhanced monitoring
system and advanced intelligent energy management system. In addition to
improvements in existing PHS technology, similar ideas are being actively studied such
as seawater usage as a reservoir, tidal barrages, and Gravity Power Module Energy
Storage (GPMES) [145]. The GPMES uses two different sized water shafts to store
energy. The electricity is consumed to pump water in the smaller shaft and raises the
position of a heavyweight piston of the more massive shaft. When the electricity is
needed, the piston is set free, and the water flow rotates the turbine to generator power.
Instead of large-scale CAES, researchers have developed mini-CAES and aboveground
CAES to increase their usability in many applications and to overcome the dependency
of the large-scale CAES on the geographical site selection [146]. Rapid development
has been found in small-scale ground CAES as an alternative to electrochemical energy
storage for the applications such as uninterrupted power supply or backup power supply.
For flywheel energy storage, the core development area should aim to investigate novel
materials for the rotor, high performance and low-loss bearings, a robust control system
and the cost of precision manufacturing processes. Currently, the strength composite
fiber materials are applied in rotor fabrication, which may have significant
improvements in rotation speed, storage capacity, power density, and reliability. The
latest bearing technology is using the high-temperature superconductor, which
significantly increases the efficiency. However, the high production cost, operational
safety issues, and high self-discharge rate still limit its usage in long-term storage
applications.
The research and development in SC mainly focus on enhancing the chemical capacitive
materials to improve the lifespan and storage capability. The latest in SC development
includes the use of carbon graphene-based electrodes and novel nanostructured
materials that can significantly improve the SC surface area and therefore storage
capacity [147], [148]. For SMES, the cost reduction of superconducting coils, the
development of novel low cryogenically sensitive coil materials, and EMS optimization
Chapter 2 Review of Energy Storage Technologies
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should be the primary issues to be addressed in order to penetrate the market share in
energy storage industry.
Electrochemical energy storages or battery technologies as one of the mainstream
energy storages for stationary energy storage applications require technology
breakthrough in enhancing the reliability and lifespan, electrode materials, fast charging
and energy management system. Among the battery energy storage technologies, Lead-
acid battery are still one of the most widely used energy storage technologies. For
research and development of new-generation Lead-acid batteries, it should mainly focus
on electrode materials for performance improvement, extending cycling times,
enhancing the deep discharge capability as well as the recycling processes of electrode
materials. At present, one of the advanced Lead-acid battery is developed by adding up
to 40% of activated carbon to the negative electrode composition, wherein the cycle life
is significantly increased by up to 2,000 times [149]–[151].
For lithium-based battery, many research works have been initiated on the innovation of
electrode and electrolyte materials to increase their power capability, energy density and
lifetime. The usage of graphene in replacing the conventional electrolyte materials has
claimed to revolutionary improves the storage capacity and charging time. The
graphene-based lithium battery is still on the early stage of research and development,
but the superior characteristics of graphene have attracted attentions from researchers
and industry [152].
NaS battery is a relatively mature technology and is often used for large-scale energy
storage projects. However, the high temperature operating requirements and eliminating
the corresponding limitations still need to be addressed [153]. The main limitations of
flow battery are the capital cost associated with electrolyte sources, battery stack
manufacture and high maintenance costs. The next generation of flow batteries could be
the structure with hybrid redox fuel cells. Shortly, it is possible to apply in electric
vehicles which makes it easier for electric vehicles to recharge energy by refueling
[118]. The hydrogen energy storage technology is still in its early stages. It requires
extensive testing and validation before it can be fully commercialized. The
improvements in system power conversion efficiency, safe operation, low-cost
Chapter 2 Review of Energy Storage Technologies
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hydrogen production, storage, and transportation processes will become the leading
research and development directions for future development [154].
In general, energy storage technology provides more flexibility and optimizes the power
system operations. In the macro view of future energy storage deployment, the trend
that forcing energy storage technologies to become a central element of the future
power system will mainly depend on the penetration level of RES, the emergence of
smart-grid development and the advancement in low-cost environment-friendly
materials [155]–[157]. Thus its future development could mainly focus on the following
areas.
Firstly, energy storage technology needs to achieve more grid integration to improve its
safety, stability, high efficiency, and reliability. With ESS integration, power electronics,
and information technologies, the electric grid is anticipated to transforming into the
decentralized structure and achieving two-way interaction in every node in the power
system including generation, transmission, distribution, and consumers’ end. This will
eventually realize the upgrade to smart-grid and form the powerful internet-style global
energy grid in the future [158], [159]. Secondly, the longevity and cost of ESS must be
improved, while having both high power density and high energy density, to provide the
auxiliary services such as backup energy, power smoothing and peak shaving for the
renewable power systems that have intermittent and unpredictable output power. Multi-
variate hybrid ESS with complementary characteristics and its optimized supporting
control system will become the enabler in achieving both high power and energy
density requirements. Finally, energy storage will be more widely used in electric
powered transportation systems such as electric vehicles, hybrid vehicles, electric-
driven trains, drones, and aerospace applications, etc. [160]–[162]. This is the highest
technical requirement for ESSs, and it usually requires them to have higher security,
longer duration, shorter charging time, faster response, lighter and cheaper.
2.6 Conclusion
The potential applications of energy storage in modern power system and residential
ESS are presented in this chapter. The desired characteristics of energy storage at a
Chapter 2 Review of Energy Storage Technologies
- 46 -
different part of the power systems are discussed to ease the selection of energy storage
for optimal performance and sustainability. The energy storage technologies in various
forms were comprehensively reviewed and compared, including the electrical
characteristics, storage capability, efficiency, and product features. The introduced
energy storage technologies include CAES, FES, PHS SC, SMES, cell battery, flow
battery, TES, and chemical energy storage. The comparative analysis of available
energy storage technologies was carried out based on storage and electrical properties,
strengths and limitations, technology maturity as well as the potential for future
development. It can be concluded that the wide spectrum of technical characteristics of
current ESS technologies can meet the requirements of different power system
operations, with a suitable combination of different ESS technologies. Finally, this
chapter also summarizes the limitations that exist in various types of energy storage
technologies and the possible future development trends. The integration of ESS
technologies in modern large-scale power system and residential applications are critical
for providing flexibility and ancillary services in smart-grid to handle the increasing
supply-demand challenges.
- 47 -
Chapter 3
Solar PV Technology and Energy Storage
in Stand-alone Power System
3.1 Introduction
The global climate change caused by greenhouse effect has motivated the development
of renewable energy based power system to replace the traditional fossil fuel energy
[163]–[165]. Among various RES technologies, solar PV technology has become one of
the most prominent and widely used technologies due to its modularity, ease of
installation, matured technology, and low operating costs [166]. The modularity of solar
panel allows large-scale centralized PV farm (up to 50MW) to be set up, and at the
same time enables decentralized PV power system such as residential building and
remote area electrification. The main disadvantages of PV power generation are: (1) the
intermittency of output power due to clouds, and (2) variability due to the day-night
cycles as well as seasonal variation. Therefore, the PV power systems, especially for the
stand-alone systems, are generally equipped with ESS to ensure stable and reliable
electricity. Over the past decades, ESSs have been widely used and indispensable in
stand-alone solar PV power generation systems.
This chapter presents an overview of PV technology and its application in power
systems, including the considerations of PV system design, solar irradiance
measurement, load profile estimation and the selection of energy storage technology. A
detailed discussion and analysis of the stand-alone PV-battery power systems will also
be provided that contains an introduction to the system topology, the design of its ESS,
Chapter 3 Solar PV Technology and Energy Storage in Stand-alone Power System
- 48 -
system modelling, numerical simulation and experimental demonstration based on a
lab-scale prototype.
3.2 Overview of solar PV technology
3.2.1 Background of solar cell
Solar cell, also known as PV cell, is a solid state device that converts sunlight directly
into electricity. The name of PV comes from the process of converting light (photons)
into electricity (voltage), which is the so-called PV effect. The PV effect was discovered
by French physicist, Becquerel, in 1839 and was first applied in silicon cell by Bell
Laboratories until 1954. The silicon cell is soon gained applications in U.S space
programs as the power system of earth-orbiting satellites owing to its high power-
generating capacity per unit weight. The space applications inspired the solar cell
development and continued to spread into varies applications ranging from powering
rural villages to feeding national grids globally. Fig. 3.1 shows the classification of solar
cell based on the material property [167]. The family of solar cells in different primary
active materials are divided into silicon solar cell, multi-compound thin film solar cell,
polymer solar cell, modified electrode layers, nano-crystalline solar cell, organic solar
cell and other solar cells with novel materials.
Fig. 3.1 Solar cell classification
Table 3.1 summarizes the efficiency of relatively mature and dominant solar cells in the
market. Mono-crystalline silicon solar cells have been widely used in the large-scale PV
Solar Cell Technologies
Wafer-based Cells
Mono-crystalline
Cells
Poly-crystalline
CellsGaInP,
GaAs, etc.
Thin Film Cells
Amorphous Silicon (a-Si)
Cells
CdTe, CZTS, CIGS, CIS, Condenser
Organic-Materials, Dye Sensitized, etc.
Chapter 3 Solar PV Technology and Energy Storage in Stand-alone Power System
- 49 -
power system. It possesses the highest conversion efficiency and performs significantly
better compared to its counterparts under medium temperature zones such as the
subtropical area [168]. Polycrystalline silicon PV cells have similar properties to
monocrystalline silicon PV cells but suffer from higher temperature sensitivity, which
reduces conversion efficiency. Although amorphous silicon PV cells are a cheaper
option, conversion efficiency is lower, in the range of 5-7%.
Table 3.1 Three main types of solar cells in the market
Solar cells Efficiency Features
Mono-crystalline Silicon 14-17% Higher efficiency but higher price
Poly-crystalline Silicon 11-14% Cheaper than mono-crystalline but less efficient
Amorphous Silicon (a-Si) 5-7% Flexible shape, cheaper, but low efficiency
3.2.2 Solar cell model
In solid-state physic, solar cell works as a classical diode with P-N junction. The
complex PV process in solar cell can be simplified as an equivalent electrical circuit
model as shown in Fig. 3.2. The summation of the output current I, the diode current ID
and the shunt-leakage current 𝐼𝑆𝐻 is equal to the photo-current 𝐼𝐿 . The series resistor
𝑅𝑆 represents the internal resistance which depends on P-N junction characteristics such
as depth, impurities and contact resistance. Due to the material imperfections of solar
cell, there is leakage current at the edge of each solar cell and it is characterized by the
shunt resistor 𝑅𝑆𝐻 and leakage current 𝐼𝑆𝐻. For an ideal solar cell, there is no series loss
(𝑅𝑆 = 0) and no leakage current (𝑅𝑆𝐻 = 𝐼𝑛𝑓𝑖𝑛𝑖𝑡𝑦 ). The efficiency of solar cell is
sensitive to 𝑅𝑆 variation and therefore, minimizing the resistance from P-N junction is
one of the research directions in solar cell to improve the conversion efficiency.
Fig. 3.2 The equivalent circuit of solar cell
Chapter 3 Solar PV Technology and Energy Storage in Stand-alone Power System
- 50 -
The output current of solar cell is given by the following equation:
𝐼 = 𝐼𝐿 − 𝐼𝑑 − 𝐼𝑆𝐻 (3.1)
The diode current 𝐼𝑑 can be calculated by the classical diode current expression:
𝐼𝑑 = 𝐼𝐷[𝑒𝑄𝑉𝑜𝑐𝐴𝑘𝑇 − 1] (3.2)
Where
𝐼𝐷 is the diode saturation current
Q is the electron charge which equals to 1.6 ∗ 10−19𝐶
A is the curve-fitting constant
k is the Boltzmann constant which equals to 1.38 ∗ 10−23J/°K
T is the temperature in °K
The shunt leakage current 𝐼𝑆𝐻 is calculated by open-circuit voltage 𝑉𝑜𝑐 and shut
resistance,
ISH =Voc
RSH
(3.3)
Where 𝑉𝑜𝑐 is obtained when there is zero load. Thus the load current is given by the
expression:
I = IL − ID[eQVocAkT − 1] −
Voc
RSH
(3.4)
The electrical characteristics of solar cell can be graphically represented by the current
versus voltage (I-V) curve and power versus voltage (P-V) curve, as shown in Fig. 3.3.
On the vertical axis, the highest current in I-V curve occurs at zero voltage when the
output terminals are connected. This is called the short-circuit current 𝐼𝑠𝑐 . On the
horizontal axis, the highest terminal voltage occurs when no load is connected, which is
called the open-circuit voltage 𝑉𝑜𝑐. These two parameters are usually given on the solar
cell datasheet. The Maximum Power Point (MPP) occurs at the knee point on the I-V
curve (marked in red circle). The I-V curve in one solar cell will vary based on the sun
irradiation.
Chapter 3 Solar PV Technology and Energy Storage in Stand-alone Power System
- 51 -
Fig. 3.3 The I-V and P-V characteristics of the solar cell
Fig. 3.4 illustrates the different I-V curves of typical solar panel. It can be observed that
the knee points of the I-V curves are shifting to the right and the corresponding MPP on
P-V curves increases as the sun irradiation increases. Therefore, keeping the solar cell to
generate electricity at MPP continually can significantly increase the overall power
efficiency. There are many MPP tracking algorithms available nowadays to maximize
the efficiency of solar PV power systems.
Fig. 3.4 V-I and P-V curves in different intensity
*
P
(W)
0 20 40 60 80 100 120 1400
5
10
1 kW/m2
Cur
rent
(A)
Voltage (V)
Array type: SunPower SPR-305-WHT; 2 series modules; 2 parallel strings
0.75 kW/m2
0.5 kW/m2
0.25 kW/m2
0 20 40 60 80 100 120 1400
500
10001 kW/m2
Pow
er (W
)
Voltage (V)
0.75 kW/m2
0.5 kW/m2
0.25 kW/m2
Chapter 3 Solar PV Technology and Energy Storage in Stand-alone Power System
- 52 -
Fig. 3.5 Solar cells, PV modules, PV panels and PV arrays
A single solar cell typically produces 1W of power with approximately 0.5 volts. A
number of them are interconnected in series and/or parallel to generate the appropriate
voltage and current levels that can be integrated to the power systems. The PV module
is formed by solar cells that are typically sealed in a protective laminate as depicted in
Fig. 3.5. The PV modules are then assembled as a PV panel to achieve the desired
voltage and power. In a large-scale PV power system, PV panels as the fundamental
unit are connected to form PV array in order to generate the desired power generation
capacity. The flexibility and modularity of solar PV allows different size of PV power
systems to be implemented, ranging from large-scale solar farm down to residential PV
power system.
3.2.3 Overview of the PV power system
The typical PV power system consists of core components such as PV array, charge
controller, ESS, power inverter and loads. Modern PV power system also includes smart
meters, AC/DC isolator, sensors, and monitoring systems to ensure system reliability
and performance optimization. In order to achieve specific goals from powering basic
electrical appliances to feeding electricity to the national grid, the PV power system can
be designed in many different topologies. PV power system can be configured either as
a grid-connected PV system or stand-alone PV power system, with and without ESS
and/or other distributed generation sources, as categorized in Fig. 3.6. Grid-connected
PV power systems operate as distributed generation networks that are interconnected
with the utility grid. It uses power electronic inverters, or Power Conditioning Unit
Solar Cell PV Module PV Panel PV Array
Chapter 3 Solar PV Technology and Energy Storage in Stand-alone Power System
- 53 -
(PCU), to convert the DC power produced by the solar cells into AC power that are
synchronized with grid voltage and frequency. With ESS integrated, grid-connected PV
power systems can operate in either grid-connected mode or islanded mode based on the
real-time generation-demand conditions.
Fig. 3.6 The classification of PV power system
Conversely, stand-alone PV power system, or off-grid PV power system, is designed to
operate autonomously and independently that are generally used to supply electricity in
isolated or remote areas. The simplest and primitive form of the off-grid PV power
system is the direct-coupled system, where the PV panel is directly connected to a DC
load, and it usually is in small power capacity. Since there is no energy storage in the
system, it only operates when sunlight is available and commonly applied in ventilation
fans, water pumping system for agriculture, etc. A complete stand-alone PV power
system contains PV panels, charge controller, power inverter, ESS and loads. Stand-
alone PV power systems are widely used for rural electrification, especially in remote
rural areas where grid connection is not economically viable. Hybrid PV power system
is one of the solutions to compensate for the variability of PV generation, where other
distributed generations such as diesel generator, wind power generator, and mini-hydro
generator are integrated.
PV Power System
Grid-connected
Without ESS
Directly connected to Grid
With ESS
Bimodal PV System
Stand-alone
Without ESS
Direct-Couple System
With ESS
DC SystemSelf-Regulating
AC System
Hybrid PV System
With other RES based system
With Diesel Generation
Chapter 3 Solar PV Technology and Energy Storage in Stand-alone Power System
- 54 -
3.3 Stand-alone PV power system
Reliable and affordable electricity is of crucial importance to ensure the quality of life.
However, according to the International Energy Agency (IEA), in 2015, nearly 1.3
billion people are not connected to the utility grid, and over 95% of them live in the
developing countries or remote rural areas [169]. Off-grid rural communities are
generally geographical dispersal, decentralized, low population density and
geographically isolated from the national grid. Due to the resource and financial
constraints, it is difficult to extend the national grid to these areas through the
conventional power transmission and distribution approach. Thus, a typical solution to
provide electricity to the remote and inaccessible area is achieved by using petrol/diesel
generators which have low initial costs but high running costs, and most importantly,
not environmental friendly. Therefore, using renewable energy based power system in
these areas is one of the practical solutions that will bring significant benefits to the
communities, especially in reducing dependence on the expensive petrol/diesel fuel and
the difficulty in transporting them. Solar PV is one of the preferred choices of RES for
remote rural electrification due to its excellent properties such as modular, easy to
install, eco-friendly, and low operating cost [170].
3.3.1 Components and system structure
Fig. 3.7 A typical stand-alone PV-battery power system
A typical configuration of stand-alone PV power system is illustrated in Fig. 3.7. It
consists of PV arrays, charge controller, energy storage, power inverter and loads. The
charge controller with Maximum Power Point Tracking (MPPT) or the one without will
Energy Storage
Charge Controller
Inverter AC Load
DC LoadDC/DC(MPPT)
Chapter 3 Solar PV Technology and Energy Storage in Stand-alone Power System
- 55 -
regulate and control the charging process from the PV arrays to energy storage [171]. In
most cases, a DC/AC power inverter is needed to convert the DC power of ESS to AC
electricity to power up basic electrical appliances such as lighting, television, washing
machines, freezers, etc. In addition, energy storage devices are needed because of the
intermittent nature of the PV output and changeable load demand. It acts as an
intermediate energy buffer compensating the generation-demand mismatch.
To design an effective stand-alone PV power system, engineers need to carry out the
on-site assessment. For example, solar irradiance measurement, user behaviour,
electricity consumption estimation, topographical and meteorological constraints.
Alongside these aspects, the social acceptance, maintenance requirement, and
environmental impacts also need to be taken into consideration before installing PV
power systems.
3.3.2 Solar power generation
Solar irradiance refers to the electromagnetic radiation that reaches the earth surface
after being absorbed, scattered, and reflected by the atmosphere in power per unit area.
The daily solar irradiance profile (sun hours) is the key parameter that determines the
total output power of the PV panels, and it is used to calculate the photo-current
generated from PV panels, as shown in Eq. (3.5) [172]:
𝐼𝐿 = 𝐼𝑠𝑐𝑅𝐺
𝐺𝑅
[1 + 𝛼𝑇(𝑇𝑐 − 𝑇𝑐𝑅)] (3.5)
where 𝐺𝑅 and 𝐺 are the reference solar irradiation and real-time solar irradiation; 𝑇𝑐𝑅
and 𝑇𝑐 is the reference solar cell temperature and real-time solar cell temperature; 𝐼𝑠𝑐𝑅 is
the solar cell short circuit current at 𝐺𝑅 and 𝑇𝑐𝑅; 𝛼𝑇 is temperature coefficient of photo
current. In the case where the ambient temperature variation is relatively small, the real-
time output current of the PV panel can be approximated from the solar radiation.
In order to evaluate and design a sustainable PV power system, it is necessary to
understand the availability and quality of solar irradiance at the targeted site. Sarawak is
the largest state in Malaysia with the total land area of 124,450 km2, with a daily
average of ambient temperature of 26.14 ⁰C and 12 hours average sunlight throughout
Chapter 3 Solar PV Technology and Energy Storage in Stand-alone Power System
- 56 -
the years [173], [174]. The tropical climate with mostly cloudy weather condition
provides average daily sun hours of about 4 to 5 hours. In most cases, the solar input
fluctuates due to the shelter of clouds. Fig. 3.8 illustrates a 7-day solar radiation profile
collected in Kuching, Sarawak, Malaysia.
Fig. 3.8 The 7-day solar irradiance in Kuching, Sarawak, Malaysia
3.3.3 Load demand estimation
In order to design a cost-effective off-grid residential PV power system, an accurate
estimation of the load profile is vital to ensure that the system can generate sufficient
energy and to prevent short battery cycling. Fig. 3.9 depicts a simple load profile
estimation method used in this work. This method is based on the demographics of local
households, the quantity, and characteristics of household appliances and users’
behaviour on daily energy consumption.
Firstly, a site survey was conducted to collect basic information about the population in
the community, living area, public space, daily work routines and behaviours, and the
types of electrical appliances. These appliances include lighting, television, refrigerator,
electric fan, and consumer electronic devices. The characteristics and usage frequency
of each electrical appliance are recorded during the site assessments. Secondly,
aggregate the collected information into a checklist, and assign values to each item
using the appropriate data. The estimated load curve will then be formed by the sum of
12.08 12.09 12.10 12.11 12.12 12.13 12.14 12.150
400
800
1200
1600
2000
2400
Days
Sola
r Rad
iatio
n (W
/m2)
Chapter 3 Solar PV Technology and Energy Storage in Stand-alone Power System
- 57 -
the values of both items. Finally, add a degree of redundancy to the results to form the
final load profile estimation.
Fig. 3.9 Assessment of load profile for a non-electrified rural community
Fig. 3.10 illustrates an example of the estimated load profile for a rural community,
Batang-Ai (1°14’20.5”N, 112°02’10.7”E), in the inner part of Sarawak using the
abovementioned method. The target site has 6 households. It is noticed that peak energy
demand occurs during noon time (between 11 AM to 2 PM) and night time (between 7
PM to 10 PM). This is because most of the power-demanding activities such as cooking
and entertainment are scheduled during these times. The estimated total load demand
per day is around 15kWh.
0 6 12 18 00
0.25
0.5
0.75
Hours of Day
Pow
er (k
W)
Additional Appliances
Community Hall
Total ConsumptionCommon Lighting
Household Use
Fig. 3.10 Estimated load profiles of the target rural site in Sarawak, Malaysia
Load profile
Households
Population Public area
Appliances
Daily activity profile
Standby consumption
Use frequency Types
Appliances list
Load curve for the appliancesTotal load curve
Step 1: Survey
Step 2: Estimation
Chapter 3 Solar PV Technology and Energy Storage in Stand-alone Power System
- 58 -
A 2kW stand-alone PV-battery-genset hybrid power system was designed and installed
at the targeted site during this research work (Appendix 1). The actual load profiles
were measured as shown in Fig. 3.11, and it demonstrates very similar electricity usage
pattern as the one estimated using the abovementioned method.
(a) 2016/10/21 (b) 2016/10/22
Fig. 3.11 Actual load profiles of the target rural site in Sarawak, Malaysia
3.4 Energy storage in stand-alone PV power system
ESS is the key component in stand-alone PV power system to balance the generation-
demand mismatch [175]. It absorbs excess energy generated by solar panels during the
off-peak period and supplies energy when PV generation is insufficient during peak
time or night time. The selection and design of ESS in stand-alone PV power system is
essential as it is one of the major cost components in a typical installation.
3.4.1 Discussion about the selection of ESS
As discussed in Chapter 2, no single energy storage technology can have all the desired
features to fulfill the criteria in any specific application scenarios. The determination for
selecting an appropriate energy storage product normally requires a series of trade-offs
and considerations. Thus the selection of suitable energy storage device for stand-alone
PV power system in remote areas normally needs to consider the following criteria:
capacity, efficiency, availability and cost, stability, and lifespan. Ideally, in remote
applications, energy storage device with small size, high efficiency, fast response,
Chapter 3 Solar PV Technology and Energy Storage in Stand-alone Power System
- 59 -
mature technology, good stability, longevity, clean and low maintenance cost will be the
preferred choice. Based on the analysis in Table 2.3, SMES and SC have relatively high
efficiency, fast response, clean, and longevity, but their energy density is low and with
high self-discharge rate. In addition, SMES is a relatively new technology and
extremely expensive due to superconductive wiring coil usage.
On the other hand, the voltage and capacity of a single SC are minimal, and it usually
requires a lot of them to connect in series and in parallel to reach the rated voltage and
rated capacity. Therefore, the entire system requires power electronic converters as the
controller to maintain the voltage balance and manage the power flow, which increases
the complexity. Thus, neither SMES nor SC is suitable as the primary energy storage in
this application. Similarly, in the hydrogen and flywheel energy storage, the issues of
relatively high cost, immature technology, high self-discharge rate (Flywheel), and the
difficulty in transporting the hydrogen to remote areas make them unsuitable for remote
off-grid applications.
Among all ESS technologies discussed above, electrochemical energy storage turns out
to be the most appropriate ESS for stand-alone PV power system. Firstly, the fluctuating
and unpredictable nature of the PV output cannot allow the nickel-based battery to
operate effectively without losing its capacity due to memory effects. Thus Nickel-
based battery also is not suitable in PV power system. While NaS battery and flow
battery provide robust lifespan and relatively low cost, but NaS battery requires high
maintenance and complicated system to ensure to the high-temperature operating
environment. Flow battery and metal-air battery are still under research and
development stage.
Till now, the Lead-acid battery and Lithium-ion battery are the two remaining ESS
options. They are both suitable for the remote applications, but Lithium-ion battery is
thermally less stable than the Lead-acid battery (safety reason) and higher initial cost,
which needs reliable SoC monitoring and control to avoid overcharging. Conversely,
the Lead-acid battery is much stable (electrically and thermally) and robust. Thus, the
Lead-acid battery is chosen as the most suitable energy storage technology for stand-
alone PV energy system as its ESS.
Chapter 3 Solar PV Technology and Energy Storage in Stand-alone Power System
- 60 -
3.4.2 Lead-acid battery and its stress factors
In a stand-alone PV-battery power system, the battery bank is often one of the most
expensive components regarding initial cost and operating cost [176]–[178]. This is
because the aging mechanism of Lead-acid batteries results from various stress factors
caused by the intrinsic characteristics of charging and discharging processes. The life-
limiting factors in the Lead-acid battery are listed below [95], [179]–[181]:
1. Prolonged low SoC;
2. Overcharging;
3. High operating temperature;
4. Frequent deep or full discharge, high depth of discharge;
5. Charging/discharging with a high C-rate;
6. Frequent charge-discharge transitions;
7. Partial cycling in low SoC.
Most of these life-limiting factors are closely related to SoC, which is the amount of
remaining available energy in the battery and expressed as a percentage of rated energy
[182], [183].
Fig. 3.12 Electrochemical reaction of the Lead-acid battery
Fig. 3.12 shows the electrochemical reaction in a typical Lead-acid battery [180].
During the discharging process, sponge lead (𝑃𝑏) is converted to lead sulfate (𝑃𝑏𝑆𝑂4)
on the negative plate and generate electrons simultaneously. The lead dioxide (𝑃𝑏𝑂2) is
converted into 𝑃𝑏𝑆𝑂4 on the positive plate and sulfuric acid (𝐻2𝑆𝑂4) is consumed in the
electrolyte. The 𝑃𝑏𝑆𝑂4 in the process of becoming the 𝑃𝑏𝑆𝑂4 will cause an increase of
the battery volume. While during the charging process, the 𝑃𝑏𝑆𝑂4 is converted back to
Porous LeadSulfuric
AcidPorous lead
DioxideLead sulfate Water Lead sulfate
Active material of
negativeplate
Electrolyte
Active material of
positive plate
Active material of
negative plate
Electrolyte
Active material of
positiveplate
Discharging
Charging
Chapter 3 Solar PV Technology and Energy Storage in Stand-alone Power System
- 61 -
𝑃𝑏𝑂2 again, and the battery volume will shrink. When the battery undergoes repeatedly
shrinkage and expansion, the inter-bonding between the 𝑃𝑏𝑂2 particles will be
gradually loosened, and eventually leading to shortened battery life. If the DoD can be
reduced, the degree of such shrinkage and expansion will be significantly reduced, and
the binding force between the lead dioxide particles will continue to be maintained, thus
increasing the lifetime of the battery [184].
Another stress factor that accelerates the performance deterioration of the Lead-acid
battery is the Charge and Discharge Rate (C-rate). High C-rate will cause the removal of
active materials on the plate and reduces the battery rated capacity and lifetime [185]. In
Fig. 3.13, the relation of the C-rate, DoD, battery rated capacity and lifecycles are
presented [186], [187]. The graphs show that the performance and cycle life of Lead-
acid battery be improved by carefully controlling the DoD and C-rate. Therefore,
mitigating the stress factors can effectively prolong the service life of the Lead-acid
battery.
(a) LA battery lifecycles vs. DoD (b) LA battery rated capacity vs. Discharge time
34
s
Fig. 3.13 The curves of the Lead-acid battery healthy and stress factors
3.5 Case study of stand-alone PV-Battery power system
A Matlab Simulink model of a 5 kW stand-alone PV-battery power system is developed
as shown in Fig. 3.14. Actual solar irradiance data recorded on typical sunny days and
partially cloudy days were used to simulate PV power generation. While the estimated
load profile (as shown in Fig. 3.10) is considered in the simulation and analysis.
Chapter 3 Solar PV Technology and Energy Storage in Stand-alone Power System
- 62 -
Fig. 3.14 Matlab Simulink model of stand-alone PV-Lead-acid battery system
0 4 8 12 16 20 0-100
-60
-20
20
60
100
Hours of Day
Cur
rent
(A)
(a) PV-Load
(b) LA Battery
Fig. 3.15 Simulation current of stand-alone PV-battery power system (sunny)
0 4 8 12 16 20 0
-60
-20
20
60
100
Hours of Day
Cur
rent
(A)
(a) PV-Load
(b) LA Battery
Fig. 3.16 Simulation current of stand-alone PV-battery power system (cloudy)
Chapter 3 Solar PV Technology and Energy Storage in Stand-alone Power System
- 63 -
The net power flow to and from the battery bank is illustrated in Fig. 3.15 (for sunny
day condition) and Fig. 3.16 (for partly cloudy day condition). The Lead-acid battery
bank (4000Ah) absorbs or supplies the net difference between the PV output and the
load demand. When its current is negative, the Lead-acid battery will be charged and
being discharged when net current is positive. as can be observed from the battery
current profiles, severe fluctuations occur during day time where PV generation is
available, even during sunny day condition.
3.5.1 Scaled prototype of stand-alone PV power system
A down-scaled prototype of stand-alone PV-battery power system was constructed to
demonstrate the operating characteristics of the Lead-acid battery experimentally. The
voltage on the DC bus is 12V, and the capacity of the Lead-acid battery is 30Ah. A
typical commercial charge controller is used to regulate the charging process from PV
to the Lead-acid battery. The experimental results in Fig. 3.17 demonstrate the battery
current profiles measured during partly cloudy weather at Swinburne University
Sarawak Campus, Kuching, Malaysia. The PV output current changes abruptly and
fluctuates randomly. The Lead-acid battery starts to charge at around 7:00 a.m. and
discharge at around 4:00 PM.
0 4 8 12 16 20 0-1.5
-1
-0.5
0
0.5
1
1.5
Hours of Day
Cur
rent
(A)
(a) LA Battery (b) PV-Load
Fig. 3.17 Experimental current of stand-alone PV-battery power system (one day)
Chapter 3 Solar PV Technology and Energy Storage in Stand-alone Power System
- 64 -
In Fig. 3.18, the 2 hours operating current can indicate that the battery closely follows
the net difference in PV and load currents. There are rapid charge/ discharge conditions,
from -1.5A to 1.5A, as well as high current charging or discharging requirements, which
has a significant adverse effect on battery life.
8
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Hours of Day
Cur
rent
(A)
(a) LA Battery (b) PV-Load
Fig. 3.18 Experimental testing of stand-alone PV-battery power system (2 hours)
3.5.2 The concept of SC/Lead-acid battery HESS
In stand-alone PV power system, the Lead-acid battery has to continuously charge and
discharge based on the fluctuating power requirement as a result of solar intermittency
and load variability. This highly dynamic charge/discharge processes are putting heavy
operation stress on the battery bank, thus accelerating performance deterioration and
aging process. Over the past decades, Battery-SC hybrid ESSs has been proposed by
many researchers for mitigating charge-discharge stress on the Lead-acid [188]–[190].
SC as an energy storage device with excellent power density, fast response time and
most importantly long cycle life, has turned out to be a great complementary energy
storage device to compensate the limitations of the electrochemical battery bank. The
primary idea of Battery-SC hybrid ESS is to allow the SC to absorb/supply the dynamic
power exchange while letting the primary battery bank in responding to the average
Chapter 3 Solar PV Technology and Energy Storage in Stand-alone Power System
- 65 -
power demand. Although the concept of HESS sounds promising, special consideration
must be taken into accounts such as topology design, control system, and energy
management strategy. The next chapter will introduce the Battery-SC HESS in details.
3.6 Conclusion
This chapter introduced solar cell technology and PV power generation systems,
including literature review, working principles, classification, and typical system
architecture. In rural electrification, stand-alone PV power systems have been widely
installed and applied. This chapter provided an overview and discussion of system
design, solar irradiance measurement, load estimation methods, system modelling, and
analysis. Based on the energy storage technology discussed in Chapter 2, the selection
of energy storage technology in the stand-alone PV power system is critically discussed
and concluded that the Lead-acid battery is still one of the most suitable ESS for remote
applications.
- 66 -
Chapter 4
Study on Battery-SC HESS: Topology,
Control Strategy, and Application
4.1 Introduction
Lead-acid battery as one of the mainstream energy storage devices used in stand-alone
PV power system suffers from short service life, despite the excellent electrical
characteristics and lower initial cost. The ESS acts as an intermediate buffer to absorb
excess energy and supply the stored energy when the power deficit. In addition, it also
plays a vital role in regulating instantaneous power variations, power quality, and
system reliability. Especially for a stand-alone PV power system, it relies heavily on
energy storage to balance the unmatched generation and power consumption profiles
[191]–[193]. For example, surge demand power to start motors in appliances can be 7 to
10 times larger than normal operation current [194], and the PV output fluctuates
dynamically due to cloud shelter on PV arrays. The fluctuating and variable power flow
could potentially accelerate the aging process of the Lead-acid battery. Thus, without
proper control, the Lead-acid battery normally can only last 3-5 years which leads to
higher operating cost [195]. Therefore, effectively prolonging the service life of Lead-
acid battery bank will have a significant economic impact on the market of the off-grid
PV power system.
Hybridization of different ESS technologies turns out to be one of the promising ways
to mitigate the battery charge-discharge stress by directing the short term power
fluctuation to another form of ESS such as the SC [196]–[198]. The SC stores electricity
Chapter 4 Study on Battery-SC HESS: Topology, Control Strategy, and Application
- 67 -
via electrons in the static electric field and possesses high power density, has short
charging-discharging time, and nearly unlimited cycle life. The battery and SC
combination has been considered in most HESS developments because of their
availability, similarity in working principle, relatively low cost and most importantly.
They complement each other’s limitations very effectively. Recently, the development
of Battery-SC HESS for residential energy storage applications is beginning to generate
positive outcomes, and it typically is connected to the power system via AC or DC
coupling [199]–[204]. Power electronic converters are used to control the power flow
among different ESS elements [205]–[207]. Depending on the complexity of the control
strategies, the use of power converters and microcontrollers can be costly [208]. Hence,
the trade-off between economic feasibility and technical advantages exist, and it is
crucial in determining the financial and technical sustainability of the system.
Various Battery-SC HESS topologies had been proposed in microgrid applications
aiming to optimally utilize the benefits of different ESS elements [209], [210]. Besides
having correct HESS topology and appropriate sizing, energy management and control
strategy of HESS is another key to improve system efficiency, maximize energy
throughput and prolong the lifetime of HESS [211]–[213]. This chapter presents a
comprehensive review and discussion of Battery-SC HESS, including their system
topologies design, electrical characteristics, energy management system, control
algorithms and applications in stand-alone PV power system.
4.2 Battery-SC HESS topologies
In Battery-SC HESS, the two ESS elements can be coupled to either a common DC or
AC bus. For stand-alone microgrid, common DC bus is the preferred choice due to
various reasons [214], [215]. First, most ESS elements and RES based generators
operate in DC voltage. Therefore, maintaining a DC bus minimizes the needs of power
converter [216]. Second, DC bus does not require synchronization which greatly
reduces the complexity of the overall system [217], [218]. As a result, DC coupling is
more efficient and lower cost than equivalent AC bus systems [219]–[222]. In general,
the topologies of the Battery-SC HESS can be classified based on the interfacing
approach, as shown in Fig. 4.1. For passive connection, the terminals of energy storage
Chapter 4 Study on Battery-SC HESS: Topology, Control Strategy, and Application
- 68 -
are directly connected to the DC bus for which the power-sharing mechanism and
response is purely determined by the electrical characteristic of the energy storage
devices. On the other hand, active HESS topologies employ active components such as
bi-directional DC/DC power converter to interface the energy storage elements from
DC bus and to actively control their power flow.
Battery-SC HESS
Passive HESS Semi-Active HESS
Full Active HESS
SC Semi-Active
Battery Semi-Active
Parallel
Cascaded
Multi-LevelHESS
Fig. 4.1 Classification of the battery-SC HESS topologies
4.2.1 Passive Battery-SC HESS
The passive connection of battery and SC modules to DC bus offers the simplest and
cheapest form of HESS [223]. It has been reported to effectively suppress transient
current under pulse load conditions, increase the peak power and reduce internal losses
[224]–[226].
Battery SC
DC Bus
Fig. 4.2 Passive HESS topology
As shown in Fig. 4.2, the battery and SC are connected to the DC bus directly, thus
sharing the same terminal voltage. The DC bus voltage is purely depending on the
battery SoC, and therefore it is highly influenced by the charge-discharge characteristic
Chapter 4 Study on Battery-SC HESS: Topology, Control Strategy, and Application
- 69 -
of the battery. In some rural microgrid applications, the battery capacity is sized up to
five days as a reserve without any external source of energy [227]. Consequently, most
of the time the battery will be cycled with relatively low DoD and charged/discharged in
a relatively low C-rate. As a result, the fluctuation in DC bus voltage will be minimal,
ensuring a relatively stable system voltage.
However, the system current will be drawn from or feed into the battery and SC based
on their respective internal resistances. Therefore, the transient power handling
capability of the SC is not optimally utilized. In addition, as the voltage variation of the
battery terminal is small, the SC will not be operating at its full SoC range which results
in poor volumetric efficiency [228].
4.2.2 Semi-Active Battery-SC HESS
To make better use of the ESS elements in Passive HESS, power electronic converters
are included between the ESS elements and DC bus. This allows the power flow to be
actively controlled [229]. In Semi-Active HESS topology, only one of the two energy
storage elements is actively controlled as illustrated in Fig. 4.3.
Battery
SC
DC Bus
DC/DC
Battery
SC
DC Bus
DC/DC
(a) SC Semi-active HESS (b) Battery Semi-active HESS
Fig. 4.3 Semi-Active HESS topologies
Fig. 4.3(a) shows the SC Semi-Active HESS topology where the SC is connected to the
DC bus through a bidirectional DC/DC converter and the battery is directly connected
to the DC bus [230]. In this topology, the bidirectional DC/DC converter isolates the SC
Chapter 4 Study on Battery-SC HESS: Topology, Control Strategy, and Application
- 70 -
from the DC bus and battery terminal. In this setting, the SC can be operated within a
wider range of voltages, which significantly improves the volumetric efficiency. The
direct connection of the battery also ensures stable DC bus voltage [231]. However, the
passive connection of the battery inevitably exposes the battery to fluctuating
charge/discharge current that has a negative effect on battery lifetime [232].
Conversely, the battery is interfaced by a DC/DC converter, while the SC is directly
connected to DC Bus in the battery Semi-Active HESS configuration as shown in Fig.
4.3(b) [199], [233]–[235]. Unlike passive and SC Semi-Active HESS topologies, the
battery current can be controlled at a relatively gentler manner regardless of the
fluctuation in the power demand. The battery terminal voltage is not required to match
the DC bus voltage, allowing flexible and efficient sizing and configuration of battery
bank. However, the volumetric efficiency of the SC is low. The linear charge/discharge
characteristic of the SC also causes large variation in the DC bus, which may result in
poor power quality and system stability. To maintain a relatively stable DC bus voltage,
the capacity of SC must be extremely large, which leads to high cost.
4.2.3 Full Active Battery-SC HESS
In Full-Active Battery-SC HESS topologies, the power flow of battery and SC are both
actively controlled via bidirectional DC/DC converters. This enhances the flexibility of
the HESS and improves the overall system performance and cycle life. Fig. 4.4 shows
two of the most common Full-Active HESS topologies, namely parallel active HESS
and cascaded active HESS. In Parallel Full-Active HESS, both battery and SC are
isolated from the DC bus by bidirectional DC/DC converters, as shown in Fig. 4.4(a). It
is one of the most common topologies in grid-scale storage applications, allowing full
control of both energy storage elements [194], [236]–[238]. With this topology, the
performance, battery life, and DC bus stability can be improved through a carefully
designed control strategy [239]. For instance, the battery, as a high energy density ESS,
can be programmed to meet the low-frequency power exchanges. The SC can be
programmed to respond to the high-frequency power surges and regulate the DC bus
voltage. The decoupling of battery and SC allows both ESS elements to operate at a
wider range of SoC that can greatly improve the volumetric efficiency of the HESS.
Chapter 4 Study on Battery-SC HESS: Topology, Control Strategy, and Application
- 71 -
Battery
SC
DC Bus
DC/DC
DC/DC
SC
DC Bus
DC/DC DC/DC
(a) Parallel Active HESS Topology
(b) Cascaded Active HESS Topology
Battery
Fig. 4.4 Active HESS topologies
In cascaded active HESS topology, two bidirectional DC/DC converters are cascaded to
isolate the battery and SC from the DC bus, as illustrated in the Fig. 4.4(b) [240]. The
bidirectional DC/DC converter that isolates the battery is normally current controlled to
provide smooth power exchange with the battery. This releases the battery from harsh
charge/discharge process due to the intermittency of renewable power generation and
load. The bidirectional DC/DC converter that isolates the SC from the DC bus is
normally voltage controlled to regulate the DC bus voltage while absorbing the high-
frequency power exchanges [241]. Since the SC has wide operating voltage, a large
voltage swing between the SC and DC bus is expected. As a result, the power losses in
the DC/DC converter will be higher as it is difficult to maintain efficiency across a wide
range of operating voltages.
4.2.4 Multi-level Battery-SC HESS
In Fig. 4.5, assuming a basic module includes either or both batteries and SC
with/without DC/DC converters, hybridization beyond two energy storage modules can
be configured in different combinations of passive, active, cascaded and/or parallel with
unique power management system and control strategy.
Chapter 4 Study on Battery-SC HESS: Topology, Control Strategy, and Application
- 72 -
ESS module can be passively/actively series/parallel connected
DC Bus
Module1
ModuleN
Module1 ModuleN
orBatt
SCDC/DC
orPassive
Basic module
Fig. 4.5 Multi-level Battery-SC HESS topology
The SC or battery can be modularized into a different voltage or power levels and
performs a good adaptability to different system requirements. This enables a more
flexible HESS in terms of system configuration and the adaptability to more
sophisticated energy control algorithms for broader power and energy applications. As
the number of power converters increases, the overall coulombic efficiency of the HESS
will decrease due to losses from the switches among the MOSFET devices. The
performance of full active HESS system is also extremely reliant on the reliability of the
DC/DC converters and their control system.
4.3 Energy management system (EMS)
4.3.1 Overview of EMS
Although the hybridization of battery and SC with different characteristics have great
potential in complementing the lifetime limitations of Lead-acid battery in stand-alone
PV power system, it creates energy management and control problems. Especially for
HESS with actively controlled DC/DC converter(s), a properly designed EMS is the key
to ensuring harmonized operation while achieving the objectives and control goals of
HESS implementation. As shown in Fig. 4.6, a complete EMS may include long-term
Chapter 4 Study on Battery-SC HESS: Topology, Control Strategy, and Application
- 73 -
energy management, medium-term energy management, and real-time energy
management. In the long-term energy management (beyond 24 hours), information such
as weather conditions, load demand status, and battery SoC are collected and analyzed
in order to generate reference control signals for the medium-term controller. Then the
medium-term EMS will focus on monitoring hourly parameter variations and operation
mode selection, as well as generating reference signals for a low-level control system
for DC/DC converters.
Fig. 4.6 The EMS with the multi-level control structure
Generally, the objectives of HESS implementation in stand-alone microgrid can be
grouped into three main categories: (i) optimizing system performance, (ii) enhancing
system reliability and (iii) lowering set-up and operating cost. Fig. 4.7 summarises the
objectives. Active HESS topology enables each ESS elements to be optimized through
an EMS.
Long-term Supervision
Medium-term Supervision
Real-time Supervision
Electrical Grid
ES1 ES2 ESnHybrid Energy Storage System
(HESS)
Real Time
1h – 1/2h
24h or Longer
Overall Cost Evaluation Storage Capacity
Load ForecastWeather Forecast
Weather Forecast (hr-Level)Mode Selection by UsersStorage Capacity (hr-Level)
Based on Energy Index Determine Suitable Mode Mode 1,2, … , n
Availability of ESS Units
Chapter 4 Study on Battery-SC HESS: Topology, Control Strategy, and Application
- 74 -
Good EMS
Performance System Reliability
HESS EfficiencyPower Quality
ESS Lifespan ExtensionDevice Protection
System Stability
Economic Feasibility
Reduce Power Conversion FrequencyEnergy Saving (Load Management) Simplicity (Structure and algorithm)
Fig. 4.7 Features and function of an efficient EMS design
The role of EMS is to maximize the benefits of HESS. Volumetric and coulombic
efficiencies have to be maximized while maintaining system stability and power quality
at the DC bus. In terms of system reliability, EMS must ensure robust system operation
in all possible loading conditions, protect the ESSs from extreme conditions and extend
the useful lifetime of the ESS elements. EMS also needs to ensure that cost of
implementation, operation and maintenance are kept low. For instance, scheduling of
diesel generator and load can be integrated into the EMS to lower the operating cost.
4.3.2 The design considerations of EMS
Fig. 4.8 depicts a typical EMS structure for a Battery-SC HESS in microgrid
applications [242]. In general, the EMS can be divided into two levels: (i) the low-level
control system regulates the DC bus voltage and controls the current flowing in and out
of ESS elements based on the reference signal generated by the high-level control
system. (ii) The high-level control system performs the power allocation strategy, SoC
monitoring and control, and other sophisticated energy management strategies to
achieve the set control goals.
Zhou et al. adopted the parallel active topology and proposed a modular HESS scheme
that splits the single battery bank into multiple smaller battery modules [243]. The SC
module and battery bank modules are interfaced to DC bus using dual-active-bridge
bidirectional DC/DC converters. The authors employed a linear filtering approach to
remove high-frequency power fluctuations and distribute the smooth power demands to
each battery modules based on their SoC level. The SC module will respond to the high-
Chapter 4 Study on Battery-SC HESS: Topology, Control Strategy, and Application
- 75 -
frequency power exchange through cascaded inner current control loop and outer
voltage control loop. A simple SoC management scheme for SC module is implemented
where the battery modules will charge the SC when the SoC level is lower than a pre-set
threshold. The EMS mainly focuses on balancing the charge/ discharge current among
different battery modules. However, it does not consider the impacts of battery SoC
variation in long-term operation, which may affect the system stability and longevity of
the battery. Moreover, the proposed modular HESS topology requires a large number of
DC/DC converters, leading to a significant increase in power loss and set-up cost.
Energy Management System (EMS)
HESS
Alg
orith
m
DC Bus
MPPT
MM
M Load
SCM
M
PV
PHESS
Current Control Voltage Control
SoC Management
MDC/DC Converter
DC/AC Inverter
Measurement
Control Signal
Measurement Signal
Batt
Power Allocation
PBATT(ref) PSC(ref)
Generation ForecastLoad PredictionWeather ForecastEnergy Market Data
Low-level ControlHigh-level Control
+-
PPV
PLoad
PPV
PLoad
Fig. 4.8 Typical EMS for stand-alone PV power system with parallel active HESS
To address the issue of high charge/discharge rate and possible response delay of the
DC/DC converter, Kollimalla et. al. adopted the linear filtering approach to decompose
Chapter 4 Study on Battery-SC HESS: Topology, Control Strategy, and Application
- 76 -
the power demand into high-frequency and low-frequency components and added a rate
limiter to prevent the battery from being damaged by the high charge/discharge rate
[194]. An additional compensator is implemented to compensate the slow response of
battery charge/discharge. The proposed EMS mainly focuses on regulating the DC bus
voltage and mitigating battery stress by limiting the battery current. The technique
assumes that all ESS elements work within the acceptable limits throughout the
operation. It does not take into consideration the SoC control of the battery. This may
cause the battery to experience deep discharge under extreme conditions, which may
lead to shorter battery lifetime.
Choi et al. presented an EMS scheme in Battery-SC HESS to achieve two objectives: (1)
to minimize the energy loss due to SC internal resistance and (2) to mitigate the
fluctuations of current flowing in/out of the battery pack [30]. The author
mathematically formulated the two objectives in order to obtain the optimal solution to
control the current flow in each ESS elements. The two objectives were formulated into
convex optimization problems, which are norm approximation and penalty function
approximation, respectively. The two problems are then combined into a single multi-
objectives function. In order to obtain the optimal solution, boundary parameters were
determined through multiplicative-increase-additive-decrease principle. The values of
the boundary parameters critically determine the feasibility and optimality of the
solution. This control strategy only considers the characteristics of ESS elements. It
does not consider the interactions between the elements and other components within
the microgrid. Thus, the resulting optimal EMS scheme tends to be for one particular
system only.
The above EMS strategies for HESS mainly focus on solving the short-term power
demand variations and power-sharing between SC and battery. However, the impact of
SoC drift in the battery is not addressed. Specifically, in a microgrid, seasonal variations
in renewable energy generation and load demand must be carefully addressed to ensure
reliable operation in all possible loading conditions. To accurately monitor the battery
SoC and address its long-term variations, Xue et al. proposed an actively controlled,
parallel connected Battery-SC HESS in PV power system that employs a multimode
fuzzy-logic power allocator to address the mismatch between supply and demand [244].
Chapter 4 Study on Battery-SC HESS: Topology, Control Strategy, and Application
- 77 -
Based on the SoC conditions of battery and SC, the fuzzy-logic controller selects the
appropriate operating mode to allocate the demand power to the energy storage devices.
To avoid overcharging or discharging the energy storage, the controller allows the
power exchange between the battery and SC and their individual power contribution to
be optimally adjusted. The EMS control strategy guarantees all energy storage devices
operate within their safe operating range and compensates transient mismatches
between power generation and load demand.
Most EMS relies on a centralized controller to manage the power flow among different
ESS elements and DC bus. Therefore, a robust communication link between
components is needed. A disruption in the communication link will lead to catastrophic
system failure. A hierarchical controller for HESS was proposed in [212] to address this
risk. In the normal operating mode, the centralized controller allocates power to ESS
modules based on their ramp rate. ESS with the highest ramp rate usually is assigned to
regulate bus voltage. In the situation where the centralized controller fails, distributed
control at individual ESS elements will be activated to ensure power system continuous
operation.
4.3.3 Advanced algorithm in EMS
Due to the complex and non-linear characteristics of battery and SC during the
charging/discharging operation, simple power allocation method such as linear filtering
may not be sufficient to effectively allocate the power demand among the energy
storage elements in HESS. Therefore, advance supervisory control algorithms for EMS
have been developed. A number of different intelligent and sophisticated control
algorithms, such as deterministic rule-based strategy, fuzzy logic control, linear
programming, genetic algorithms, dynamic programming, neural network, self-adaptive
algorithms, etc. have been reported in the literature [155], [245]–[247]. Fig. 4.9
illustrates an overview of the classification of existing EMS algorithms in HESS. The
EMS algorithms are generally categorized into two main classes which are rule-based
approaches and optimization-based approaches [248]–[250].
Chapter 4 Study on Battery-SC HESS: Topology, Control Strategy, and Application
- 78 -
Intelligent Algorithms for EMS Control
Rule-Based Optimization-Based
Fuzzy Logic Global Optimization (Off-line)
Real-time Optimization (On-Line)
Power FollowerState Machine
Typical Fuzzy LogicFuzzy Predictive
Deterministic
Fuzzy Adaptive
Linear ProgrammingDynamic ProgrammingStochastic DPGenetic AlgorithmAdaptive Fuzzy Rule BasedEvolutionary MethodsSimulated Annealing
Frequency DecouplingRobust ControlOptimal Predictive
Thermostat (On-Off)
Supervised Learning Machine (SLM)
Fig. 4.9 Classification of intelligent algorithms for EMS supervisory control
(1) Rules-Based Approach
Rule-based approach controls the power exchange of HESS based on rules that are
derived from mathematical models and experiences [251]–[253]. The rule-based
approach is an effective method for real-time energy management widely used in HESS
applications. In thermostat control strategy, the battery operates with constant power at
its optimal efficiency point, and it will be turned on or off according to the lower and
upper SoC limits. In power follower control strategy, the battery is set as the primary
energy storage, and the EMS will adjust the battery charge/ discharge power that
follows the power demand. As a secondary ESS, the SC covers the difference between
the power demand and battery response.
Unlike thermostat and power follower control strategy, the state machine control
strategy uses multiple rules to control the power flow in HESS. The pre-defined rules
can be designed based on the allowable upper and lower SoC limits of SC and battery,
maximum charge and discharge rates, load and generation powers, etc. Based on the
real-time operational states of the HESS, power generation and power demand, the
algorithm selects the appropriate operation mode to optimize the power distribution
between SC and battery.
Chapter 4 Study on Battery-SC HESS: Topology, Control Strategy, and Application
- 79 -
The deterministic rule-based control strategies are widely adopted due to its simplicity,
less computationally intensive and great reliability [251], [254]–[257]. However, the
rules are generally designed based on the initial state of the ESS elements. This may not
accurately reflect the actual conditions of the elements in the long run. Therefore, the
fuzzy logic control strategy as shown in Fig. 4.10 is introduced. Similar to the
deterministic approaches, the rules in fuzzy control are also pre-defined based on
mathematical model and empirical data. The transition between different rules is
determined by the fuzzy-rules and membership functions which results in smoother,
more flexible and logical operation compared with deterministic rule-based approaches
[244], [258]–[260]. Fuzzy rule-based control algorithms can be integrated with other
intelligent algorithms to form a hybrid control strategy which further improves the
performance of EMS in HESS [236], [261]–[263].
Start
Measure and Collect Data
Fuzzification
InferenceEngine
Defuzzification
Results
Output Membership
Functions
Fuzzy Rules(Relation between
Input&Output)
Solar Irradiance Weather Condition Load Profile SoC & Power Flow Voltage & Currentetc.
Input Membership
Functions
(Eg.)
Fig. 4.10 Fuzzy logic flowchart
(2) Optimization-Based Approach
Optimisation-based EMS employs modern optimization algorithms, such as linear
programming (if the system is convex and could be mathematically represented via a set
Chapter 4 Study on Battery-SC HESS: Topology, Control Strategy, and Application
- 80 -
of linear functions), dynamic programming (both deterministic and stochastic),
evolutionary methods such as genetic algorithm, simulated annealing, and particle
swarm optimisation [264]–[269]. These algorithms can be classified into global
optimization (offline) and real-time optimization (on-line). Unlike the rule-based
approaches, modern optimization algorithms and their associated optimization processes
are often sophisticated that require heavy computation capability [248]. In genetic
algorithms, optimal power allocation in HESS can be achieved by analyzing the genetic
processes as shown in Fig. 4.11. Based on the pre-defined fitness functions, the
determined percentage and mutation rate, the genetic algorithms controller will
iteratively search for optimal solutions until the number of iteration exceeds the pre-set
values.
Meteorological Conditions(Solar Irradiance,
Weather Conditions, etc.)
Economical Data (Electricity Tariff, Price of
PV, ESSs, Load Profile, etc.)
Optimization Constraints and Termination Criteria
Pre-Defined Fitness Function and
GA Parameters (Selection Percentage, Mutation Rate, etc )
Create Random Initial Population
Evaluate Fitness of Each Solution
Selection
Crossover
Mutation
Select Next Generation
Stopping Criteria Check
Return the Best Solution
Iterative Procedure
NOYES
OUTPUT
INPUT
Fig. 4.11 Genetic algorithm flowchart
Linear programming optimization approach is commonly used for systems that are
convex and could be mathematically represented via a set of linear functions.
Conversely, dynamic programming employs multiple iteration loops that are designed
Chapter 4 Study on Battery-SC HESS: Topology, Control Strategy, and Application
- 81 -
to execute the backward iteration from time step N to 1, as shown in Fig. 4.12 [252].
Every loop is employed to calculate the corresponding value as shown in the flowchart.
The cost-to-go function will be updated at each time step, and the iterative processes
will end when optimal solution of the objective function is obtained. One computation
cycle will generate one state, and the whole process can be called state iterations.
Finally, the dynamic programming approach will generate a look-up table that contains
the optimal decision variable at each state. In general, trade-offs in technical
requirements and economic feasibility need to be carefully considered in the design and
development of HESS control algorithms. Advanced EMS can provide high power
quality and improve system stability. However, system complexity and hardware
requirements will add to the overall system cost.
Start
Iteration from Time Step N to 1
Determine Load Demand and System Parameters
Iteration of State Variables
Determine Constraints for Control Variable
Iteration of Control Variable
Evaluate Cost-To-Go Function
Finish Iteration of Control Variable
Determine Optimal Control Decision at Current Time
Step and States
Finish Iteration of All States at Time Step k
Finish Iteration of All Time Steps from N to 1
End
INPUT
OUTPUT
NO
NO
NO
YES
YES
YES
Fig. 4.12 Dynamic programming flowchart
4.4 Analysis and discussion
There are varieties of HESS topologies and the associated energy management and
control strategies used in the microgrid applications aiming to improve the system
Chapter 4 Study on Battery-SC HESS: Topology, Control Strategy, and Application
- 82 -
operation from multiple aspects. However, there is no single unique HESS solution
suitable for all microgrid applications. To determine an ideal HESS design and control
strategy, a detailed analysis of the system requirements, end-user expectations,
physical/environmental constraints, and both technical and economic feasibilities have
to be considered.
4.4.1 HESS topologies and EMS
The development of HESS is expected to progress in two directions: (i) robust and
reliable HESS in small-scale stand-alone microgrids specifically for remote or isolated
sites, (ii) independent and intelligent medium in the large-scale grid-connected power
system that is part of the smart-grid architecture. Most researches on HESS are focused
at reducing the stress on the batteries while maintaining power quality, improving HESS
efficiency and lowering set-up cost. For greater controllability, active HESS topology is
commonly used. However, this increases the system complexity and most importantly,
creating additional uncertainty and making the power system more vulnerable to
components failures [270].
On the contrary, as the most straightforward HESS structure, passively connected
Battery-SC HESS provides a simple and robust way to relieve battery operating
pressure, but at the same time reduces system efficiency and controllability. In this
topology, the SC acts as a Low-Pass Filter (LPF) for battery, and the filtering effect is
inherently dependent on the internal resistance of the Battery-SC HESS as well as the
installed SC capacitance, which also implies the low volumetric efficiency of the SC.
Between the Full-Active and Passive HESS topologies, Semi-Active HESS enables
active control of power flow with less active components used.
For the Multi-level HESS topologies, there exist many sophisticated designs and control
strategies in the literature. In [271], the battery bank is made up of micro-bank modules,
each with its own DC/DC converter and EMS. A control strategy that dynamically
configures the battery modules is put in place to optimize the use of the modules and for
greater system efficiency. A similar concept was also proposed in [272], where banks of
varied energy storage elements and battery types were used with a global charge
Chapter 4 Study on Battery-SC HESS: Topology, Control Strategy, and Application
- 83 -
allocation algorithm that controls the power flow between the storage banks. With the
careful use of power electronic converters, the configurable and modular HESS could
be one of the future trends in the development of EMS in microgrid applications.
4.4.2 Summary of the advantages of Battery-SC HESS
The Battery-SC HESS was initially designed to take the benefits of SC such as fast
response, long life, and high power density and make it absorb high-frequency currents,
thereby protecting the battery from the surge, intermittent, variable currents and
effectively increasing its service lifetime. The advantages are listed below:
a) Battery lifetime extension
The integration of SC helps to reduce transient fluctuations in the battery power profile
which releases its operation stress. This enables the battery lifetime extension owing to
the reduction in the peak power requirement. In the battery-only system, it needs to
cover peak power demand, leading to increased temperature which also results in
lifetime reduction.
b) Higher energy efficiency
The relatively low ramp rate of traditional chemical battery could result in the mismatch
in surge power demands, which can have a negative impact on power quality and
energy efficiency. In HESS, the SC acts as a load balancing device for the battery when
the SC transmits or receives energy at peak power. The battery current profile will
become closer to the average or smooth power, with small RMS value and fewer peaks.
Consequently, the HESS satisfies all power demands with higher energy efficiency,
while the battery operates in a much healthy current profile.
c) Size reduction
For the same power requirements, the battery-only system needs to oversize the battery
capacity to cater for the short term surge demand [273].
d) Less environmental impact and cost saving
Chapter 4 Study on Battery-SC HESS: Topology, Control Strategy, and Application
- 84 -
As the lifespan of the battery increases, the operating cost of a stand-alone PV-battery
system can be significantly reduced, thus minimizing the needs to recycle the battery
frequently.
4.4.3 AC coupled and hybrid AC/DC PV-HESS power system
The aforementioned HESS configurations in this chapter are mainly based on the DC
bus. In the rural area, the remote distance for connection to the grid and lack of
advanced control hardware maintenance requires the power system to have a robust
control solution [274]–[276]. DC coupled stand-alone PV-battery power system is
ideally suited for remote rural electrification, and they are generally small-scale in the
range of 2-10kW [277]–[280]. In the large-scale microgrid, AC coupling is common to
allow seamless integration with utility grid and minimize losses in power transmission
effectively [217].
AC Load
DC Distributed Generation (PV)AC/DC
AC Distributed Generation
(Wind, Hydro)AC/DC/AC
AC Bus
Battery
HESS
SC
Controller
DC/AC
DC/AC
PVCharge
Controller(MPPT)
DC Load
DC Bus
AC Load
DC/AC
Battery
DC/DC
Passive/Semi/Active HESS
SC
Controller
DC/DC
DC/AC
DC/AC
Interlinking Converters(ILCs)
AC Bus
AC Load
Passive/Semi/Active HESSAC/DC
DC Distributed Generation (PV)AC/DC
AC Distributed Generation (Wind)AC/DC/AC
Utility Grid
DC-Coupled AC-Coupled
Utility Grid
(a) AC Coupled PV Power System With other RES or Gird Connection
(b) Hybrid AC/DC PV Power System With other RES or Gird Connection
Fig. 4.13 The stand-alone PV-HESS power system expansion
Chapter 4 Study on Battery-SC HESS: Topology, Control Strategy, and Application
- 85 -
Fig. 4.13 demonstrates a hybrid AC-DC PV power system that consists of both DC and
AC buses [202], [267]. For possible future requirement, the hybrid AC-DC bus coupling
architecture allows integration of AC-based renewable generation technologies (such as
wind turbines and hydropower), distributed generations as well as the utility grid. The
connection of two buses is the interlinking converters. In the DC-coupled part, the
control system will be designed to regulate the voltage and manage the power flow
within HESS. The situation is different in AC bus, where the HESS is required to
control the frequency and voltage simultaneously and transfer the energy between the
DC and AC in a bidirectional way.
4.4.4 HESS topologies and EMS in rural electrification
Rural communities are usually located far from the grid where technical support is
usually limited. Therefore, the implementation of power systems in these areas
prioritizes simplicity, stability, robustness, and low maintenance requirements, rather
than efficiency, intelligence, and functionality. Thus simple, inexpensive, and robust
HESS are desirable and shall be prioritized in the design process for remote application.
Therefore, the Battery-SC HESS structure with fewer DC/DC converters will be more
favorable, such as Passive HESS and SC Semi-Active HESS configurations. The next
chapter will provide a comprehensive discussion and analysis on Battery-SC HESS in
stand-alone PV power systems, including system topology, control system,
mathematical modelling, numerical simulation, and experimental verification.
4.5 Conclusion
This chapter introduced the concept of Battery-SC HESS, including the system
topologies, control strategies and possible applications in the stand-alone power system.
The existing HESS topologies are categorized into four main categories, which are
Passive HESS, Semi-Active HESS, Full-Active HESS, and Multi-level HESS. Their
corresponding characteristics, strengths, weaknesses and possible applications were
discussed and compared. The availability of actively controlled components enabled the
use of EMS to manage the power exchange within the HESS. The operation stress of the
battery can be reduced while maintaining a high level of power quality and reliability.
- 86 -
Chapter 5
Battery-SC HESS for Stand-alone PV
Power System in Rural Electrification
5.1 Introduction
In Battery-SC HESS, the net current exchange is decomposed into two or more
frequency components. Ideally, the primary large battery bank will supply the low-
frequency component which often represents the nominal current profile. As a high
power density ESS, the SC absorbs the high-frequency power exchange from the
intermittency of solar power generation and sudden change in load demand. As
discussed in Chapter 4, many variations of Battery-SC HESS designs and their
associated EMS have been proposed by researchers over the past decades. These HESS
designs are generally intended to serve large-scale utilities, smart-grid, electric vehicles,
and other high power applications, and they normally require extensive sensing,
computation, and communication, which significantly increase the system complexity
and implementation.
This chapter presents a comprehensive study and discussion on the potential Battery-SC
HESS topologies and energy management strategies in stand-alone PV power system,
especially for rural electrification purposes. The targeted HESS topologies are presented
and discussed in sequence from the simplest passive HESS structure to complex active
topology. Theoretical analysis and numerical simulation of the HESS under
consideration are presented to demonstrate the feasibility and effectiveness of mitigating
battery stresses in stand-alone PV power system based on case studies of a remote
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 87 -
community in Sarawak, Malaysia. Novel evaluation method based on a battery healthy
cost model is proposed to perform technical comparison and to demonstrate the
improvement in primary battery health, thus the economic impact study. Experiments
have been carried out and presented to verify the theoretical analysis.
5.2 Selected HESSs for stand-alone PV power system in rural electrification
Based on the discussion in Chapter 4, HESS topologies can be categorized regarding the
number of ESS elements, the strategies of power-sharing among ESS elements and the
interfacing methods, as summarised in Fig. 5.1.
Multi-level HESS
Battery-Supercapacitor HESS
Passive HESS
Batt SC
DC Bus
Bi-directional power electronic converter
(a)
Active Power Allocation
Supercapacitor Semi-Active HESSParallel Full Active HESS
Batt
SC
DC Bus
DC/DC
Batt
SC
DC Bus
DC/DC
DC/DC
Cascaded Full Active HESS
Batt SC
DC Bus
DC/DC DC/DC
Battery Semi-Active HESS
Batt
SC
DC Bus
DC/DC
(b) (d)
(e)
2 ESS elements > 2 ESS elements
DC Bus
DC/DC DC/DCSC Batt
(c)
(f) ESS module can be passively/actively series/parallel connected
DC Bus
Module1
ModuleN
Module1 ModuleN
orBatt
SCDC/DC
orPassive
Basic module
DC/DC
Passive Power Allocation
Fully Active Semi Active
Fig. 5.1 Classification of the Battery-SC HESS topologies
In rural electrification, most stand-alone PV power systems are geographically isolated
[281], [282]. As a result of the high maintenance cost and limited technical support,
system robustness turns out to be one of the most important considerations when
designing HESS. Therefore, fully active HESS topologies may not be suitable for this
rural electrification application. Conversely, HESS that can perform basic power
management with minimal active components interfacing secondary ESS module(s) will
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 88 -
be the preferred choice. Among all HESS topologies presented above, the Passive HESS
(Fig. 5.1(a)) and SC Semi-Active HESS (Fig. 5.1(d)) are two potential configurations for
stand-alone PV power system in rural electrification. However, the two topologies have a
common weakness that both of them require installing a large capacitance of SC to
effectively absorb the fluctuating current, which leads to higher costs. Thus, based on Fig.
5.1(f), a novel Multi-level HESS configuration with passively connected primary ESS
(extended from the SC Semi-Active HESS) is proposed, as illustrated in Fig. 5.2. This
topology can have both benefits of passive HESS and semi-active HESS, the installed 2nd
battery can replace part of SC which contribute an economic save. Their operation
characteristics and control strategy in stand-alone PV power system will be discussed
and compared in the following subsections.
2nd Battery
SC
DC Bus
DC/DC
DC/DC
1st Battery
Fig. 5.2 Multi-level HESS topology
5.3 Stand-alone PV power system with selected HESSs
To evaluate and compare the power-sharing capability of the selected HESS designs for
rural applications, the responses of different ESS elements are investigated with pulse
current loads. Matlab Simulink models of the respective HESS topologies and their
control algorithm are developed, and the integration of these HESSs in stand-alone PV
power system are discussed and demonstrated.
5.3.1 With Passive HESS
As the simplest topology of HESS, the Passive Battery-SC HESS can help to smooth
the original current curve of Lead-acid battery directly and is the easy to install in
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 89 -
standalone PV power system. The Passive HESS can be modelled by an equivalent
circuit model as shown in Fig. 5.3 [283]. The SC is modelled as a large capacitance C
with an equivalent series resistance 𝑅𝑠𝑐 with a finite initial voltage 𝑉𝑠𝑐𝑖 in SC. The
Lead-acid battery is modeled as a constant voltage source VLA with an equivalent series
resistance RLA, where Lead-acid is its short name.
+
-
vBus(t)RLARsc
C
vLA
iLA(t)
iBus(t)
ILA(s)
Rsc
VLA /s
Vsc /C
1 /sC
+
-
IBus(s)
VBus(s)
isc(t) Isc(s)
RLA
+
-
ZTh(s)
VTh(s)
IBus(s)
VBus(s)
vsci : SC initial voltage
(a) Time Domain (b) Frequency Domain (c) Equivalent Circuit
Fig. 5.3 The equivalent circuit of the Passive HESS
The Thevenin equivalent voltage VTh(s) and impedance ZTh(s) in frequency domain are
[222], [228]:
𝑉𝑇ℎ(s)=RLA
s+
RLA
RLA+R𝑠𝑐
*𝑣𝑠𝑐𝑖 − 𝑣𝐿𝐴
s+ 1(RLA+R𝑠𝑐)C
(5.1)
𝑍𝑇ℎ(𝑠) = RLA𝑅𝑠𝑐
RLA + 𝑅𝑠𝑐
∗𝑠 +
1𝑅𝑠𝑐𝐶
𝑠 +1
(RLA + 𝑅𝑠𝑐)𝐶
(5.2)
where s is the complex variable. In order to study the behavior of the HESS when there
is a source/load, and suddenly fluctuate from one level to another, this study assumes a
pulse source. The analysis method is as follows. For repetitive pulse load input, the
periodic load current, 𝑖𝐵𝑢𝑠(𝑡) can be expressed as:
𝑖𝐵𝑢𝑠(𝑡) = 𝐼𝐵𝑢𝑠 ∑[∅(𝑡 − 𝑘𝑇) − ∅(𝑡 − (𝑘 + 𝐷)𝑇)]
𝑁−1
𝑘=0
(𝑘 = 0,1,2, … ) (5.3)
where D is the duty ratio of the input signal, ∅(𝑡) is the step function. To transfer the
function with variable time to its frequency domain with complex variable s, the
corresponding Laplace transform of 𝑖𝐵𝑢𝑠(𝑡) is:
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 90 -
𝐼𝐵𝑢𝑠(𝑠) = 𝐼𝐵𝑢𝑠 ∑ [𝑒−𝑠𝑘𝑇
𝑠−
𝑒−𝑠(𝑘+𝐷)𝑇
𝑠]
𝑁−1
𝑘=0
(𝑘 = 0,1,2, … ) (5.4)
Then the voltage drop across the impedance 𝑍𝑇ℎ(𝑠) for the given current 𝐼𝐵𝑢𝑠(𝑠):
𝑉𝑍(𝑠) = 𝐼𝐵𝑢𝑠(𝑠) ∗ 𝑍𝑇ℎ(𝑠) = RLAR𝑠𝑐𝐼𝐵𝑢𝑠
RLA + 𝑅𝑠𝑐
∑ [𝑠 +
1𝑅𝑠𝑐𝐶
𝑠 +1
(𝑅𝐿𝐴 + 𝑅𝑠𝑐)
∗𝑒−𝑠𝑘𝑇 − 𝑒−𝑠(𝑘+𝐷)𝑇
𝑠]
𝑁−1
𝑘=0
(5.5)
The terminal voltage in the frequency domain can be expressed as:
𝑉𝐵𝑢𝑠(𝑠) = 𝑉𝑇ℎ(s) − 𝑉𝑍(𝑠) (5.6)
𝑉𝐵𝑢𝑠(𝑠) =𝑉𝐿𝐴
𝑠+
RLA𝑅𝑠𝑐
RLA + 𝑅𝑠𝑐
∗𝑣𝑠𝑐𝑖 − 𝑣𝐿𝐴
s+ 1(RLA+R𝑠𝑐)C
− 𝑉𝑍(𝑠) (5.7)
and its expression in the time domain via inverse Laplace transforms:
𝑣𝐵𝑢𝑠(𝑡) = 𝑣𝐿𝐴 +RLA
RLA + 𝑅𝑠𝑐
∗ (𝑣𝑠𝑐𝑖 − 𝑣𝐿𝐴) ∗ 𝑒−
𝑡(RLA+𝑅𝑠𝑐)𝐶
− RLA𝐼𝐵𝑢𝑠 ∑
[ (1 −
RLA
RLA + 𝑅𝑠𝑐
𝑒−
𝑡−𝑘𝑇(RLA+𝑅𝑠𝑐)𝐶) ∅(𝑡 − 𝑘𝑇)
−(1 −RLA
RLA + 𝑅𝑠𝑐
𝑒−
𝑡−(𝑘+𝐷)𝑇(RLA+𝑅𝑠𝑐)𝐶)∅(𝑡 − (𝑘 + 𝐷)𝑇)
] 𝑁−1
𝑘=0
(5.8)
Finally, the battery current 𝑖𝐿𝐴(𝑡) and SC current 𝑖𝑠𝑐(𝑡) can be obtained as:
𝑖𝐿𝐴(𝑡) =𝑣𝐿𝐴 − 𝑣𝐵𝑢𝑠(𝑡)
𝑅𝑏
= −(𝑣𝑠𝑐𝑖 − 𝑣𝐿𝐴)
RLA + 𝑅𝑠𝑐∗ 𝑒
−𝑡
(RLA+𝑅𝑠𝑐)𝐶
+ 𝐼𝐵𝑢𝑠 ∑
[ (1 −
RLA
RLA + 𝑅𝑠𝑐𝑒
−𝑡−𝑘𝑇
(RLA+𝑅𝑠𝑐)𝐶)∅(𝑡 − 𝑘𝑇) −
(1 −RLA
RLA + 𝑅𝑠𝑐𝑒
−𝑡−(𝑘+𝐷)𝑇(RLA+𝑅𝑠𝑐)𝐶)∅(𝑡 − (𝑘 + 𝐷)𝑇)
]
𝑁−1
𝑘=0
(5.9)
𝑖𝑠𝑐(𝑡) = 𝑖𝐵𝑢𝑠(𝑡) − 𝑖𝐿𝐴(𝑡) (5.10)
Since the SC and battery will share the same terminal voltage with DC bus at steady
states, where 𝑣𝑠𝑐𝑖 = 𝑣𝐿𝐴, then their current in steady state are:
𝑖𝐿𝐴𝑠𝑠(𝑡) = 𝐼𝐵𝑢𝑠 ∑
[ (1 −
RLA
RLA + 𝑅𝑠𝑐
𝑒−
𝑡−𝑘𝑇(RLA+𝑅𝑠𝑐)𝐶)∅(𝑡 − 𝑘𝑇) −
(1 −RLA
RLA + 𝑅𝑠𝑐
𝑒−
𝑡−(𝑘+𝐷)𝑇(RLA+𝑅𝑠𝑐)𝐶)∅(𝑡 − (𝑘 + 𝐷)𝑇)
] 𝑁−1
𝑘=0
(5.11)
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 91 -
𝑖𝑆𝐶𝑠𝑠(𝑡) =RLA𝐼𝐵𝑢𝑠
RLA + 𝑅𝑠𝑐
∑ [𝑒
−𝑡−𝑘𝑇
(RLA+𝑅𝑠𝑐)𝐶 ∗ ∅(𝑡 − 𝑘𝑇) −
− 𝑒−
𝑡−(𝑘+𝐷)𝑇(RLA+𝑅𝑠𝑐)𝐶 ∗ ∅(𝑡 − (𝑘 + 𝐷)𝑇)
]
𝑁−1
𝑘=0
(5.12)
At time 𝑡 = (𝐷 + 𝑘)𝑇, the pulse load current steps from low to high resulting in a net
change in HESS current. Assume the maximum current occurs at N approaching infinity,
the battery peak current can be simplified as:
𝑖𝐿𝐴𝑝 = 𝐼𝐵𝑢𝑠(1 − 𝜀) (5.13)
The parameter 𝜀 defines the current allocation relationship between the battery and the
SC at the peak current, and its expression is:
𝜀 =RLA
RLA + 𝑅𝑠𝑐
∗ 𝑒−
𝐷𝑇(RLA+𝑅𝑠𝑐)𝐶 ∗
1 − 𝑒−
(1−𝐷)𝑇(RLA+𝑅𝑠𝑐)𝐶
1 − 𝑒−
𝑇(RLA+𝑅𝑠𝑐)𝐶
(5.14)
The parameter also indicates that the peak current from the battery will always be less
than 𝐼𝐵𝑢𝑠 when SC is connected. If there is no SC, 𝜀 = 0, and then 𝑖𝐿𝐴𝑝 = 𝐼𝐵𝑢𝑠 , which
means that there is no enhancement and the battery alone absorbs all the charging
current. Eq. (5.13) also expresses the relation between the battery current and DC bus
current at specific time. In the case where the Lead-acid battery operates under a rated
current, the DC bus current can be calculated as:
𝐼𝐵𝑢𝑠 =1
(1 − 𝜀)𝐼𝐿𝐴𝑅𝑎𝑡𝑒𝑑 = 𝜕 ∗ 𝐼𝐿𝐴𝑅𝑎𝑡𝑒𝑑 (5.15)
To evaluate the peak power enhancement in HESS, assuming the instantaneous HESS
peak power occurs at rated current:
𝑃𝐻𝐸𝑆𝑆𝑝 = 𝐼𝐵𝑢𝑠 ∗ 𝑉𝐵𝑢𝑠 = 𝜕 ∗ 𝐼𝐿𝐴𝑅𝑎𝑡𝑒𝑑 ∗ 𝑉𝐵𝑢𝑠 = 𝜕 ∗ 𝑃𝐿𝐴𝑅𝑎𝑡𝑒𝑑 (5.16)
Eq. (5.16) shows the peak power in the HESS increases as the parameter ∂ is greater
than 1, while the SC passively connects in parallel.
The computation model of Passive HESS in Matlab Simulink is shown in Fig. 5.4. A
12Ah Lead-acid battery and 10 Farad SC are connected in parallel to the pulsed current
load. The input pulsed current load is set to 5 amps, 50% duty cycle and cycling period
of 10s. Fig. 5.5 presents the simulation results of the capability of power sharing between
the Lead-acid battery and SC for Passive HESS topology. At the rising edge, the SC
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 92 -
responses rapidly due to the relatively low time constant. The SC will be discharged
immediately once the step current drop to zero and it allows the battery discharge in
relatively smooth curve. On the other hand, the battery slowly picks up over time and
supply the demanded current. The results show minor effect on the power-sharing in the
passively connected Battery-SC HESS for which the power-sharing only occurs within
fractions of seconds. Additionally, the power-sharing capability of Passive HESS is fixed
based on the internal parameters of the two ESS elements.
Fig. 5.4 Matlab Simulink model of Passive HESS
15 20 25 30 35 40
-4
-2
0
2
4
6
8
Time (s)
Cur
rent
(A)
(a) LA Battery(b) SC(c) Pulse Load
Fig. 5.5 Pulse load response of Passive HESS
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 93 -
A schematic diagram of the integration of a passive Battery-SC HESS in a typical stand-
alone PV power system is illustrated in Fig. 5.6. The Lead-acid battery is usually the
primary energy storage. The charge controller is modeled as a unidirectional DC/DC
converter with a MPPT system and two control switches for interfacing the HESS and
the load. A diesel/petrol generator usually is integrated as a backup and dispatchable
power source in case of system failure or when additional energy is required.
Fig. 5.6 Stand-alone PV power system with Passive HESS
5.3.2 With SC Semi-Active HESS
For SC Semi-Active HESS (Fig. 5.1(d)), the equivalent circuit model in the time domain
and frequency domain are presented in Fig. 5.7.
+
-
vBusRLARsc
CvLA
ic iLA
iBus
Ic(s) Ib(s)
Rc
VLA /s
Vc /C
1 /sC
IBus(s)
VBus(s)
DC/DC DC/DCisc Isc(s)
RLA
vsci : SC initial voltage
Vsc
vc
vsc
(a) Time Domain (b) Frequency Domain
ηsc η
sc
Fig. 5.7 The equivalent circuit of the SC Semi-Active HESS
DC/DC(MPPT)
Charge ControllerDC Bus DC
Load
ACLoad
Inverter
Supercapacitor
Diesel Generator
Lead-acid battery
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 94 -
By neglecting the dynamic characteristics, the DC/DC converter is simplified and
represented as parameters of efficiency 𝜂𝑠𝑐 and voltage transfer rate Ƙsc [222]. Thus the
SC terminal voltage and current in real time before DC/DC converter is expressed as:
𝑖𝑐(𝑡) =Ƙ𝑠𝑐
𝜂𝑠𝑐
𝑖𝑠𝑐(𝑡) = 𝑖𝐵𝑢𝑠(𝑡) − 𝑖𝐵𝑢𝑠(𝑡)𝐿𝑃𝐹 (5.17)
𝑣𝑐 =𝑣𝑠𝑐
Ƙ𝑠𝑐
=𝑣𝑏𝑢𝑠
Ƙ𝑠𝑐
(5.18)
where the 𝑖𝐵𝑢𝑠(𝑡)𝐿𝑃𝐹 is the filtered 𝑖𝐵𝑢𝑠(𝑡). When pulse signal 𝑖𝐵𝑢𝑠(𝑡) is loaded, the SC
current and the battery current on DC bus are:
𝑖𝐵𝑢𝑠(𝑡) = 𝐼𝐵𝑢𝑠 ∑[∅(𝑡 − 𝑘𝑇) − ∅(𝑡 − (𝑘 + 𝐷)𝑇)]
𝑁−1
𝑘=0
= 𝑖𝑠𝑐(𝑡) + 𝑖𝐿𝐴(𝑡) (5.19)
𝑖𝑠𝑐(𝑡) =𝜂𝑠𝑐
Ƙ𝑠𝑐
𝑖𝑐(𝑡) =𝜂𝑠𝑐
Ƙ𝑠𝑐
[𝑖𝐵𝑢𝑠(𝑡) − 𝑖𝐵𝑢𝑠(𝑡)𝐿𝑃𝐹] (5.20)
𝑖𝐿𝐴(𝑡) = 𝐼𝐵𝑢𝑠 ∑[∅(𝑡 − 𝑘𝑇) − ∅(𝑡 − (𝑘 + 𝐷)𝑇)]
𝑁−1
𝑘=0
−𝜂𝑠𝑐
Ƙ𝑠𝑐
[𝑖𝐵𝑢𝑠(𝑡) − 𝑖𝐵𝑢𝑠(𝑡)𝐿𝑃𝐹] (5.21)
Assuming the peak current will occur at the end of the pulse duty cycle, when 𝑡 =
(𝑘 + 𝐷)𝑇 . Considering the efficiency factor of DC/DC converter, 𝜂𝑠𝑐 , then the
maximum current drawn from the battery can calculated by the following expression,
𝑖𝐿𝐴𝑝 = 𝐼𝐵𝑢𝑠 −𝜂
𝑠𝑐
Ƙ𝑠𝑐
[𝑖𝐵𝑢𝑠(𝑡) − 𝑖𝐵𝑢𝑠(𝑡)𝐿𝑃𝐹] (5.22)
Thus the peak current of battery is reduced by the SC current which is actively
controlled by DC/DC converter. As a result, mitigation in battery stress due to surge
current can be achieved.
The Matlab Simulink model for SC Semi-Active HESS was constructed as shown in Fig.
5.8. The parameters for SC, Lead-acid battery and the input pulsed current are set
identical to those in Passive HESS (Fig. 5.4). A LPF is used to decompose the pulse
load into two different frequency components. The generated signal from the higher one
is used to control the DC / DC converter. Inside the grey box, the Proportional-Integral
(PI) controller is implemented to track the reference signal, while the remaining of the
current demand will be responded by the passively controlled Lead-acid battery. The
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 95 -
advantage of actively controlled SC module is that the time constant of the response can
be adjusted to utilize the SC module better. Also, the isolation of the SC module from
the DC bus allows wider variation in SoC that significantly improves the volumetric
efficiency.
Fig. 5.8 The Matlab Simulink model of the SC Semi-Active HESS
15 20 25 30 35 40-6
-4
-2
0
2
4
6
8
Time (s)
Cur
rent
(A)
LA BatterySCPulse Load
Fig. 5.9 Pulse load response of the SC Semi-Active HESS
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 96 -
Fig. 5.9 shows the simulation results for power-sharing between Lead-acid battery and
SC in the Semi-Active setting. The pulse load is successfully decomposed into two
different frequencies by the LPF. Since the introduction of DC/DC converter and
simulation limitation, the current profile is changed into the shape with minor high
frequency oscillation, which is different in Passive HESS. When the pulse load becomes
5A, the SC is discharged immediately to meet the pulse requirement. When the pulse
becomes 0A, then the SC is quickly charged to absorb excess power. Throughout the
process, the battery can be slowly discharged and charged at its own rate. The sum of
the charge and discharge from the two energy storage elements is equal to the value of
the pulse load. However, due to the unavoidable time delay of the active component and
controller, there is an inrush current when there is a step change in load current.
Fig. 5.10 depicts the same stand-alone PV power system with SC Semi-Active HESS as
the energy storage. The Lead-acid battery is directly connected to the DC bus, while the
SC is interfaced with a bi-directional DC/DC converter. The net change in current is
measured and a Pulse Width Modulation (PWM) signal with the appropriate duty cycle
DSC is generated by the controller to control the power flow of SC.
Fig. 5.10 The stand-alone PV power system with SC Semi-Active HESS
DC/DC(MPPT)
Charge Controller
DC/DC
Inverter
DC Bus
ACLoad
-
DCLoad
Lead-acid Battery Storage
SupercapacitorDiesel
Generator
Energy Management Unit
(EMU)Filtration-Based Controller (FBC)
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 97 -
Ppv
Pload
+-
PHESS Decomposition Methods(eg. LPF)
+-
PSC(ref)
PSC(ref)1/VSC
ISC(ref)PI PWM
D+-
ISC
Switching Signal(SC converter)
(a) Power Allocation Strategy
(b) Linearized Model of the Current Control Loop
Fig. 5.11 Power allocation strategy for the SC Semi-Active HESS
Its control scheme is illustrated in Fig. 5.11 where the demanded power PHESS is
resolved by using decomposition methods such as LPF, and the high-frequency
component of the power exchange will be used as the reference signal PSC(ref) for SC. A
carefully tuned current tracker (PI controller) is used to control the power flow from SC.
When selecting the bandwidth of the LPF, a trade-off exists between the smoothness of
battery current IBatt and the capacity of SC. For instance, a relatively low cut-off
frequency in LPF will generate a smoother IBatt but requires larger SC capacity as well
as higher power rating of active components in DC/DC converter.
5.3.3 SC/Lithium-ion/Lead-acid battery Multi-level HESS
+
-
RLi-ion
CvLi-ion
isc iLi-ion iBus
DC/DCDC/DC
RLA
iLA
vLA
RLi-ion
VLi-ion/s
DC/DCDC/DC
RLA
Ic(s)
Rc
Vc /C
1 /sC
IBus(s)
VLA/s
ILA(s)
ILi-ion(s)
vBus VBus(s)
Rsc
η
ic ir
Isc(s)
Ir(s)
ηsc Li-ion
vc
vsc Vsc VLi-ionvLi-ion
vsci : SC initial voltage
(a) Time Domain (b) Frequency Domain
η ηsc Li-ion
Fig. 5.12 The equivalent circuit model of the Multi-level HESS
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 98 -
To maximize the advantages of the previous two topologies, this study proposed the
novel Multi-level HESS topology, and the equivalent circuits are illustrated in the Fig.
5.12. The three types of ESS elements are Lead-acid battery, Lithium-ion battery, and
SC. The Lead-acid battery is the main energy storage component, Lithium-ion battery is
the intermediate battery, and SC is the third one. The terminal voltage of SC and its
current can be expressed as:
𝑣𝑠𝑐 =𝑣𝑠𝑐
Ƙ𝑠𝑐
=𝑣𝑏𝑢𝑠
Ƙ𝑠𝑐
(5.23)
𝑖𝑐(𝑡) =Ƙ𝑠𝑐
𝜂𝑠𝑐
𝑖𝑠𝑐(𝑡) = 𝑖𝐵𝑢𝑠(𝑡) − 𝑊1 ∗ 𝑖𝐵𝑢𝑠(𝑡)𝐿𝑃𝐹1 − {[𝑖𝐵𝑢𝑠(𝑡) − 𝑤1 ∗ 𝑖𝐵𝑢𝑠(𝑡)𝐿𝑃𝐹1]}𝐿𝑃𝐹2 (5.24)
and for the Lithium-ion battery,
𝑣𝐿𝑖−𝑖𝑜𝑛 =𝑣𝑟
Ƙ𝐿𝑖−𝑖𝑜𝑛
=𝑣𝑏𝑢𝑠
Ƙ𝐿𝑖−𝑖𝑜𝑛
(5.25)
𝑖𝑟(𝑡) =Ƙ𝐿𝑖−𝑖𝑜𝑛
𝜂𝐿𝑖−𝑖𝑜𝑛
𝑖𝐿𝑖−𝑖𝑜𝑛(𝑡) = {[𝑖𝐵𝑢𝑠(𝑡) − 𝑤1 ∗ 𝑖𝐵𝑢𝑠(𝑡)𝐿𝑃𝐹1]}𝐿𝑃𝐹2 (5.26)
where the 𝜂𝑠𝑐, 𝜂𝐿𝑖−𝑖𝑜𝑛, 𝐾𝑠𝑐 and 𝐾𝐿𝑖−𝑖𝑜𝑛 are the efficiencies and voltage transfer rates of
the corresponding DC/DC converters respectively, W1 is the scaling factor that set the
proportion of Lithium-ion battery capacity in total power demand. For pulse load
response, the pulsed input current, Lead-acid battery, Lithium-ion battery and SC
currents on are:
𝑖𝐵𝑢𝑠(𝑡) = 𝐼𝐵𝑢𝑠 ∑[∅(𝑡 − 𝑘𝑇) − ∅(𝑡 − (𝑘 + 𝐷)𝑇)]
𝑁−1
𝑘=0
= 𝑖𝐿𝐴(𝑡) + 𝑖𝐿𝑖−𝑖𝑜𝑛(𝑡) + 𝑖𝑠𝑐(𝑡) (5.27)
𝑖𝑠𝑐(𝑡) =𝜂𝑠𝑐
Ƙ𝑠𝑐
𝑖𝑐(𝑡) (5.28)
𝑖𝐿𝑖−𝑖𝑜𝑛(𝑡) =𝜂𝐿𝑖−𝑖𝑜𝑛
Ƙ𝐿𝑖−𝑖𝑜𝑛
𝑖𝑟(𝑡) (5.29)
𝑖𝐿𝐴(𝑡) = 𝐼𝑜 ∑[∅(𝑡 − 𝑘𝑇) − ∅(𝑡 − (𝑘 + 𝐷)𝑇)]
𝑁−1
𝑘=0
−𝜂𝑠𝑐
Ƙ𝑠𝑐
𝑖𝑐(𝑡) −𝜂𝐿𝑖−𝑖𝑜𝑛
Ƙ𝐿𝑖−𝑖𝑜𝑛
𝑖𝑟(𝑡) (5.30)
Similarly, assuming the peak power demand still occurs at the moment 𝑡 = (𝑘 + 𝐷)𝑇,
and the maximum current drawn from the Lead-acid battery can be expressed in Eq.
(5.31) when N tends to infinity,
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 99 -
𝑖𝐿𝐴𝑝 = 𝐼𝐵𝑢𝑠 −𝜂𝑠𝑐
Ƙ𝑠𝑐
𝑖𝑐(𝑡) −𝜂𝐿𝑖−𝑖𝑜𝑛
Ƙ𝐿𝑖−𝑖𝑜𝑛
𝑖𝑟(𝑡) (5.31)
Fig. 5.13 depicts the Matlab Simulink model of Multi-level HESS and its EMS. The
parameters for Lead-acid battery module, SC module, and pulse load are kept identical
as the one in Passive HESS and SC Semi-Active HESS. The additional Lithium-ion
battery module has a capacity of 2 Ah, and the scaling factor W1 is set to 0.85. This
value is set as an example in this section, but in different applications, it can be
dynamically changed according to specific needs.
Fig. 5.13 The Matlab Simulink model of the Multi-level active HESS
The responses of the Lithium-ion battery, Lead-acid battery, and SC are depicted in Fig.
5.14. SC is programmed to respond to transient currents, while the Lithium-ion battery
responses to the medium frequency component during current variation and supplying a
small portion of the current demand. Due to the discrete simulation steps, high
frequency ripples are observed in simulation results. The DC/DC converters controls
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 100 -
current variation and allow the SC/Lithium-ion operate at their corresponding curve.
When the pulse load suddenly rises to 5A, the SC is rapidly discharged to 5A to provide
this instantaneous power, and then slowly reduce the discharge rate until 0A. At this
time, the Lithium-ion battery starts to discharge and faster than the Lead-acid battery.
After the Lead-acid battery is slowly discharged to a certain value, the Lithium-ion
battery begins to reduce the discharge rate. When the pulse load suddenly drops to 0A,
the SC instantaneously absorbs the 5A currents from the Lead-acid battery and Lithium-
ion battery. Meanwhile, the Lithium-ion battery changes its status from the discharged
state to the charged state. The Lead-acid battery slowly reduces the discharge rate until
the next pulse period. The series of above actions enable the reduction in peak current
for the passive Lead-acid battery bank which contributes to the cycle life of the battery.
Since the DC/DC converter controls the Lithium-ion battery and the SC, the inrush
current still exists as the one in the Semi-Active HESS. However, in the pulse load test,
the instantaneous increase of the current is the extreme conditions and rare in the actual
system. In a stand-alone PV power system, such a situation is not going to occur, so the
problem of inrush current will not affect the operation of the HESS.
0 5 10 15 20 25 30-6
-4
-2
0
2
4
6
8
Time (s)
Cur
rent
(A)
Li-ion BatteryLA BatteryPulse LoadSC
Fig. 5.14 Pulse load response of the Multi-level active HESS
Fig. 5.15 illustrates the stand-alone PV power system with Multi-level Battery-SC HESS
in which three different energy storage devices are utilized for better stress mitigation. In
this setting, two actively controlled complementary ESS elements (SC and Lithium-ion
battery) are connected in parallel with the passively connected primary Lead-acid battery.
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 101 -
The combination of SC and Lithium-ion modules enhances the stress mitigation
capability by covering a wider spectrum of current fluctuation as well as supply part of
the nominal current demand, which enables a more stable charge-discharge process and
peak current reduction in the primary Lead-acid battery bank.
Fig. 5.15 Stand-alone PV power system with Multi-level HESS
Ppv
Pload
+-
PHESS LPF(Primary)
+ -
+-
PSC (ref)
LPF (Secondary)
W1
PLi-ion (ref)
(a) Power Allocation Strategy
PSC(ref) 1/VSCISC(ref)
PI PWMD+
-
ISC
Switching Signal(SC Converter)
PLi-ion(ref) 1/VLi-ionILi-ion (ref)
PI PWMD+
-
ILi-ion
Switching Signal (Li-ion Battery Converter)
(b) Linearized Model of the Current Control Loop
Fig. 5.16 Power allocation strategy for the Multi-level HESS
DC/DC(MPPT)
Charge ControllerDC Bus
-
Supercapacitor DC/DC
Li-ion Battery DC/DC
Inverter ACLoad
DCLoad
Lead-acid Battery Storage
Diesel Generator
Energy Management Unit
(EMU)Filtration-Based Controller (FBC)
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 102 -
The associated power allocation strategy is shown in Fig. 5.16. Two LPFs are cascaded
to decompose the net power demand into three different frequency ranges. The highest
frequency PSC(ref) will be used as the reference signal to control the power flow of the SC
module. While the medium frequency component PLithium-ion(ref) will be the reference for
Lithium-ion battery module. A scaling factor W1 is proposed to set the proportion of
Lithium-ion battery load in total power demand.
5.4 Numerical simulations in stand-alone PV power system
To evaluate the effectiveness of the selected HESS in mitigating battery stress in stand-
alone PV power system, Matlab Simulink models of 5kW stand-alone PV power system
with different HESS are developed, and simulations have been carried out with actual
solar irradiance data and estimated load profile from the targeted site.
5.4.1 Solar irradiance and load profiles for case studies
Fig. 5.17 and Fig. 5.18 show the PV output based on the 24-hour solar irradiance data
recorded for a typical (a) sunny day and (b) cloudy day at Kuching Sarawak.
0 4 8 12 16 20 00
1
2
3
4
5
6
Hours of Day
Pow
er (k
W)
PV output in Sunny Day
Fig. 5.17 The PV output in sunny day
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 103 -
0 4 8 12 16 20 00
1
2
3
4
5
6
Hours of Day
Pow
er (k
W)
PV output in Cloudy Day
Fig. 5.18 The PV output in cloudy day
This section uses the forecasted daily scaled-up load profile that using the methodology
in Chapter 3 as load demand in the following numerical simulations. The simulation is
executed in 5kW stand-alone PV power system, and thus the estimated load profile is
scaled up into Fig. 5.19 where will have 12 households for 30 people with similar
electricity usage pattern, same place in Batang-Ai (1°14’20.5”N, 112°02’10.7”E). The
peak power demand is around 2.7kW and total load demand per day is around 30kWh.
0 6 12 18 00
0.5
1
1.5
2
2.5
3
Hours of Day
Pow
er (k
W)
Community HallTotal ConsumptionHousehold UseCommon Lighting
Fig. 5.19 Estimated load profiles of the target rural site in Sarawak, Malaysia
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 104 -
5.4.2 Results of simulations
Chapter 3 has introduced the simulation results of the battery-only in a stand-alone PV
power system, showing the PV output characteristics and current profiles of the battery
in sunny and cloudy weather conditions. With the same stand-alone PV power system,
the selected HESS topologies will be simulated and analyzed individually under the
same PV output and load profile in the following section.
Table 5.1 lists the parameters of the Matlab Simulink model used in the simulation. For
a fair comparison, the primary Lead-acid battery was kept identical for the four different
cases, and the rated voltage is 12 volts, and the installed Lithium-ion battery module is
400Ah with 12V rated voltage.
Table 5.1 Model parameters for different HESS under simulation
HESS System Topology Primary Battery Capacity (Ah) Complimentary Energy Storage Capacity
Battery-only 4000Ah (Lead-acid) - Passive HESS 4000Ah (Lead-acid) 1000F (SC)
SC Semi-Active HESS 4000Ah (Lead-acid) 1000F (SC) Multi-level HESS 4000Ah (Lead-acid) 400Ah (Lithium-ion) + 200F (SC)
a. Passive HESS
Fig. 5.20 Matlab Simulink model of Passive HESS
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 105 -
Fig. 5.20 illustrates the Matlab Simulink model of stand-alone PV power system with
Passive HESS. An ideal PV array with MPPT charge controller is considered in the
simulation of PV power generation. The simulation results for sunny and cloudy
weather conditions are shown in Fig. 5.21 and Fig. 5.22, respectively. The SC in sunny
day condition shares a small portion and normally operates between -5A to 5A. While
in cloudy day condition, the SC operates within a larger range between -20A to 20A.
With SC integrated, the Lead-acid battery current profiles show insignificant
improvement compared to the battery-only system (Fig. 3.15 and Fig. 3.16).
0 4 8 12 16 20 0-100
-60
-20
20
60
100
Hours of Day
Cur
rent
(A)
(a) PV-Load(b) LA Battery (c) SC
Fig. 5.21 Current profiles of sunny day
0 4 8 12 16 20 0-100
-60
-20
20
60
100
Hours of Day
Cur
rent
(A)
(a) PV-Load(b) LA Battery (c) SC
Fig. 5.22 Current profiles of cloudy day
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 106 -
b. Semi-Active HESS
The Matlab Simulink model for the SC Semi-Active HESS is developed as illustrated in
Fig. 5.23. Identical SC with 1000F is connected to DC bus with a bidirectional
buck/boost DC/DC converter. For power allocation, the LPF with a time constant
T=300s is employed to decompose the power demand from the DC bus. The LPF
divides the net power demand into high and low-frequency components. The low-
frequency parts are passively covered by the primary Lead-acid battery, while the SC is
programmed to respond to the high frequency fluctuating current actively.
Fig. 5.23 Matlab Simulink model of SC Semi-Active HESS
Compares to results in Passive HESS, the current profiles in Fig. 5.24 and Fig. 5.25 are
significantly smoothed. In sunny day, the SC operation range is extended to ±20A. The
effectiveness of actively controlled SC module is even more apparent in cloudy day
condition, as shown in Fig. 5.25. The sharp change in solar irradiance due to cloud
shelters caused the PV generated current to vary severely throughout the day. The
operating range of SC current is about ±60A under cloudy day condition. This
significantly improved the SC utilization rate compared to Passive HESS.
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 107 -
0 4 8 12 16 20 0
-60
-20
20
60
100
Hours of Day
Cur
rent
(A)
(a) PV-Load(b) LA Battery (c) SC
Fig. 5.24 Current profiles of sunny day
0 4 8 12 16 20 0
-60
-20
20
60
100
Hours of Day
Cur
rent
(A)
(a) PV-Load(b) LA Battery (c) SC
Fig. 5.25 Current profiles of cloudy day
c. Multi-level HESS
The Matlab Simulink model with Multi-level HESS is shown in Fig. 5.26. The Lead-
acid battery remains identical as in Passive HESS and Semi-Active HESS. The SC
capacity is reduced to 200F, and the additional Lithium-ion battery module is sized at
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 108 -
400Ah. The net power demand is split into three frequency components with two
cascaded LPF (see Fig. 5.16). The time constants are set to 300s and 150s, respectively.
The scaling factor W1 is set to 0.85 which indicates that the Lithium-ion battery module
is designed to cover 15% of the average power demand, while absorbing the medium
frequency fluctuation.
The SC module is programmed to absorb the highest frequency component, while the
primary Lead-acid battery bank will passively cover the remaining power demand.
Significantly smoothed primary Lead-acid battery current profiles can be observed in
Fig. 5.27 and Fig. 5.28. The SC handles the rapid oscillations and Li-ion battery handles
great oscillations. While the Lead-acid battery takes care of the averaged nominal
current demand. The SC operates within ±60A during the daytime, while the Lithium-
ion battery absorbs part of the fluctuations (±20A) and at the same time shares a portion
of the nominal load. The Lead-acid battery is significantly smoothed with a reduction in
peak current as a result of the power-sharing capability of the Lithium-ion battery
module.
Fig. 5.26 Matlab Simulink model of Multi-level HESS
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 109 -
0 4 8 12 16 20 0
-60
-20
20
60
100
Hours of Day
Cur
rent
(A)
(a) PV-Load(b) LA Battery (c) SC(d) Li-ion Battery
Fig. 5.27 Current profiles of sunny day
0 4 8 12 16 20 0
-60
-20
20
60
100
Hours of Day
Cur
rent
(A)
(a) PV-Load(b) LA Battery (c) SC(d) Li-ion Battery
Fig. 5.28 Current profiles of cloudy day
d. SoC variation in SC
Fig. 5.29 and Fig. 5.30 present the SoC variation in SC for Passive HESS, Semi-Active
HESS, and Multi-level HESS, respectively. With the capacity of 1000F in Passive HESS,
only less than 10% of the SoC is utilized because of the shared terminal voltage with
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 110 -
battery. Conversely, with the same 1000F capacitance, the decoupled SC terminal voltage
with DC/DC interface in Semi-Active topology, approximately 55% of the SoC is
utilized for both sunny and cloudy conditions.
0 4 8 12 16 20 0
40
60
80
100
Hours of Day
SC S
tate
of C
harg
e (%
)
(a) Passive HESS(b) Semi-active HESS(c) Multi-level HESS
Fig. 5.29 SoC variation of SC in three different scenarios (sunny day)
0 4 8 12 16 20 0
40
60
80
100
Hours of Day
SC S
tate
of C
harg
e (%
)
(a) Passive HESS(b) Semi-active HESS(c) Multi-level HESS
Fig. 5.30 SoC variation of SC in three different scenarios (cloud day)
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 111 -
As for the Multi-level HESS, the SoC variation ranges from 25% for the sunny day and
55% for the cloudy day, with a much-reduced capacity of 200F. Since the lifetime of SC
usually is much longer than Lithium-ion battery, and its initial cost is also higher, there is
a tradeoff about the installation of SC between Semi-Active HESS and Multi-level HESS.
In long-term applications, the Multi-level HESS needs to replace Lithium-ion battery
regularly while Semi-Active HESS would not need it. On the other hand, in short-term
applications, the lifetime of Lithium-ion battery would satisfy the requirements and
effectively prolongs the primary battery lifetime similar to Semi-Active HESS which
requires 5 times more SC installation with a much higher price.
5.4.3 Battery health assessment and financial analysis
a. Cost function
The simulation results presented above demonstrate the effectiveness of different HESSs
in mitigating the Lead-acid battery stress compared to the conventional battery-only
system. Based on the phenomenon in Lead-acid battery current profile, the
charge/discharge rate, surge and fluctuating current, deep discharge effect and
charge/discharge transition rate will be the main life-limiting factors. To quantify the
effectiveness and extend the improvements of the selected HESS topologies for the
Lead-acid battery operation environment under different weather conditions, a battery
health cost function is proposed in this study as shown in Eq. (5.32), including the sum
of real-time current square, the differential of current, square of DoD, times count of
charge/discharge transition and the calendrer lifetime of battery:
𝐶𝑜𝑠𝑡(𝑇) = ∑ 𝑛1[𝑖𝑏(𝑡)]2
𝑇
𝑡=0
+ ∑ 𝑛2 |𝑑𝑖𝑏(𝑡)
𝑑𝑡|
𝑇
𝑡=0
+ 𝑛3[𝑚𝑎𝑥(𝑏(𝑡)) − 𝑚𝑖𝑛(𝑏(𝑡))]2
+ ∑𝑛4 |1 ; 𝑖𝑓 [𝑖𝑏(𝑡) ∙ 𝑖𝑏(𝑡 − 1) < 0]
0 ; 𝑖𝑓 [𝑖𝑏(𝑡) ∙ 𝑖𝑏(𝑡 − 1) ≥ 0] +
𝑇
𝑡=0
𝑛5𝑇𝑦𝑒𝑎𝑟 (5.32)
where T is the total operating time, 𝑖𝑏(𝑡) is the battery current, 𝑏(𝑡) is the SoC of
battery, while the 𝑛1, 𝑛2, 𝑛3, 𝑛4 and 𝑛5are positive constants. Five life-limiting factors
are considered based on the lifetime characteristics of Lead-acid battery. The first term
quantifies the negative impact of charge/discharge rate (C rate). The second term
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 112 -
evaluates the accumulation of the negative extent on Lead-acid battery when subjected
to surge and fluctuating current. The third term quantifies the impact of deep discharge.
During the day, due to unpredictable power demand from PV output or load users,
Lead-acid battery may frequently switch between charging state and discharging state,
which accelerates the cycle life of Lead-acid battery. Therefore, the fourth term
penalizes the impact of the charge/discharge transition. The last term indicates the
calendar life of the battery, which is assumed to be constant over time. The aging
process of Lead-acid battery is a fairly complex chemical phenomenon caused by many
factors. It is very difficult to establish an accurate mathematical model and quantify the
extent of their impact. The formulated cost function intends to relatively measure the
impact on battery health for comparison among the HESS under consideration.
b. Battery health assessment in different weather conditions
This section will conduct a health assessment of the Lead-acid battery based on the
current profiles in different HESSs. The coefficient n2 and n4 are set to 0.3 indicating
the strong negative impact of current fluctuation and frequent charge-discharge
transitions due to the intermittent solar power. While n1 and n3 are set to 0.15 and 0.2
respectively to quantify the damaging impacts of the charge/discharge rate and deep-
discharge. The effect of calendar life n5 is usually much lower compared to the other
factors, and therefore it is set to 0.05. The assessment is executed under two different
weather conditions, which thoroughly presents the improvement of battery health with
different HESS topologies. Different load profile will be used during these two days.
1. Sunny day condition
The cumulative impacts (24 hours) of the life-limiting factors for different HESS are
shown in Figs. 5.31-5.33, respectively. The impact of calendar life is not presented
because they are assumed to be identical for the Lead-acid batteries of similar size. In Fig.
5.31, the Multi-level HESS performs the lowest value while the other three systems have
almost the same value. This is because the Lithium-ion battery shares a part of the
current so that the Lead-acid battery can work under the lower charge/discharge rate. Fig.
5.32 shows the extent to which HESS reduces drastic current fluctuations, or dynamicity,
in Lead-acid battery throughout the day. In general, a significant reduction in battery
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 113 -
health cost can be observed in Semi-Active HESS and Multi-level HESS. The Multi-
level HESS with 200F SC performs equally well compared to SC Semi-Active HESS
with 1000F SC. In the case of Passive HESS, since the terminal voltage of the SC is
limited by the terminal voltage of the Lead-acid battery, the power-sharing capability is
insignificant. As for the penalty on DoD (Fig. 5.33), Multi-level HESS demonstrates the
least impact on battery health cost due to the power-sharing capability of Lithium-ion
battery module.
0 4 8 12 16 20 00
2
4
6
8
10
12
14
16
18
Hours of Day
LA b
atte
ry c
harg
e/di
scha
rge
rate
(a) Battery-Only(b) Passive HESS(c) Semi-active HESS(d) Multi-level HESS
n1 : 0.15
Fig. 5.31 The results of the charge/discharge rate (sunny day)
0 4 8 12 16 20 00
200
400
600
800
1000
Hours of Day
Dyna
mic
ity o
f LA
batte
ry c
urre
nt
(a) Battery-Only(b) Passive HESS(c) Semi-active HESS(d) Multi-level HESS
n2 : 0.3
Fig. 5.32 The results of the dynamicity (sunny day)
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 114 -
0 4 8 12 16 20 050
60
70
80
90
Hours of Day
Stat
e of
Cha
rge
(%)
(a) Battery-Only [DoD : 30.78%](b) Passive HESS [DoD : 30.67%](c) Semi-active HESS [DoD : 30.74%](d) Multi-level HESS [DoD : 27.58%]
Fig. 5.33 The results of the SoC (sunny day)
Fig. 5.34 shows the impact of charge-discharge transitions on battery health. It can be
seen that SC Semi-Active performs slightly better than the Multi-level HESS. Generally,
both Semi-Active HESS and Multi-level HESS significantly reduce the impact of
fluctuating current compared to systems with battery-only and Passive HESS.
0 4 8 12 16 20 00
0.5
1
1.5
2
2.5
3
Hours of Day
LA b
atte
ry c
harg
e/di
scha
rge
tran
sitio
n
(a) Battery-Only(b) Passive HESS(c) Semi-active HESS(d) Multi-level HESS
n3 : 0.2
Fig. 5.34 The results of the charge/discharge transition (sunny day)
The normalized cumulative battery health costs of the different HESS settings in sunny
day condition are shown in Fig. 5.35. The results indicate that the Multi-level HESS
reduces about 50.1% of the battery health cost compared to conventional battery-only PV
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 115 -
power system in sunny day condition. Followed by the SC Semi-Active HESS, it
demonstrates 43.4% reduction in sunny day, while only 6.2% reduction in battery health
cost for Passive HESS.
0 4 8 12 16 20 00.2
0.4
0.6
0.8
1
Hours of Day
Cos
t (T)
(a) Battery-Only(b) Passive HESS(c) Semi-active HESS(d) Multi-level HESS
Max : 0.499
Max : 0.566
Max : 0.938
Max : 1.000
Fig. 5.35 Normalized results of cost function throughout the sunny day
2. Cloudy day condition
The results of the first four individual factors in cloudy day condition are presented in
Figs. 5.36-5.39.
0 4 8 12 16 20 00
2
4
6
8
10
12
14
16
18
Hours of Day
LA b
atte
ry c
harg
e/di
scha
rge
rate
(a) Battery-Only(b) Passive HESS(c) Semi-active HESS(d) Multi-level HESS
n1 : 0.15
Fig. 5.36 The results of the charge/discharge rate (cloudy day)
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 116 -
Similar to results in sunny day, the Multi-level HESS recorded the lowest cost due to the power-sharing capability of Lithium-ion battery module.
0 4 8 12 16 20 00
200
400
600
800
1000
Hours of Day
Dyn
amic
ity o
f LA
bat
tery
cur
rent
(a) Battery-Only(b) Passive HESS(c) Semi-active HESS(d) Multi-level HESS
n2 : 0.3
Fig. 5.37 The results of the dynamicity (cloudy day)
Similar patterns are observed on dynamicity, DoD and charge-discharge transitions.
0 4 8 12 16 20 050
60
70
80
Hours of Day
LA b
atte
ry S
tate
of C
harg
e (%
)
(a) Battery-Only [DoD : 26.28%](b) Passive HESS [DoD : 26.16%](c) Semi-active HESS [DoD : 26.08%](d) Multi-level HESS [DoD : 23.37%]
Fig. 5.38 The results of the SOC (cloudy day)
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 117 -
0 4 8 12 16 20 00
2
4
6
8
10
12
14
Hours of Day
LA b
atte
ry c
harg
e/di
scha
rge
tran
sitio
n
(a) Battery-Only(b) Passive HESS(c) Semi-active HESS(d) Multi-level HESS
n3 : 0.2
Fig. 5.39 The results of the charge/discharge transition (cloudy day)
The normalized cumulative battery health costs of the different HESS settings in cloudy
day condition are shown in Fig. 5.40.
0 4 8 12 16 20 0
0.2
0.4
0.6
0.8
1
1.2
1.4
Hours of Day
Cos
t (T)
(a) Battery-Only(b) Passive HESS(c) Semi-active HESS(d) Multi-level HESS
Max : 1.164
Max : 0.491
Max : 1.308
Max : 0.529
Fig. 5.40 Normalized results of cost function throughout the cloudy day
Setting the battery health cost of battery-only setting in the sunny day as the reference,
the battery-only system in cloudy day condition is 1.308 which is 30.8% more than the
same setting in sunny day. This is because the relatively heavier PV power fluctuation
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 118 -
in cloudy day has a larger impact on battery health, thus higher battery health cost. By
comparing the battery health cost in cloudy day condition, the Multi-level HESS
manages to reduce the battery health cost by nearly 62.5%, followed by a reduction of
59.6% in SC Semi-Active HESS, and 11% reduction in Passive HESS setting.
c. Financial analysis
The estimated annual battery cost (365 days) for different systems and their
corresponding cost reduction are calculated and presented in Table 5.2.
Table 5.2 Financial analysis under different modes
Operation mode
Weather condition
Battery Capacity
(kWh)
Initial Cost
1
($)
Battery Health Cost
Cost(T) 2
Estimated Life
Cycle
Cost / cycle ($)
Estimated Annual Battery Cost ($)
Cost Reduction
4
LA Battery-only
Sunny 48 (LA) 12288 1.000 500 24.58 8971.70 0 Cloudy 48 (LA) 12288 1.308 382 32.17 11742.05 0
Passive HESS
(SC 1000F)
Sunny 48 (LA) 12288 0.938 533 23.50 8577.5 4.4%
Cloudy 48 (LA) 12288 1.164 429 28.64 10453.6 11%
SC Semi-Active HESS (SC 1000F)
Sunny 48 (LA) 12288 0.566 883 13.92 5080.8 43.4%
Cloudy 48 (LA) 12288 0.529 945 13.00 4745.00 59.6%
Multi-level HESS
(SC 200F)
Sunny 48 (LA) 12288 0.499 1002 13.26 4839.9 +
255.5(Lithium-ion) = 5095.4
43.2% 4.8 (Li-ion) 1392 - 2000
3 0.70
Cloudy 48 (LA) 12288 0.491 1018 12.07 4405.55 + 255.5(Li-
ion) = 4661.05 60.3% 4.8 (Li-ion) 1392 - 2000
3 0.70
#Note 1 – Initial cost of Lead-acid battery ($256/kWh) and Lithium-ion battery ($290/kWh) are considered.[269] #Note 2 – Typical life cycle / Cost of battery utilization; (typical life cycle for Lead-acid – 500 cycles, Lithium-ion – 4000 cycles and SC >100,000 cycles)[269] #Note 3 – Estimated to perform 50% of the expected lifecycles of the Lithium-ion battery when Lead-acid battery is replaced #Note 4 – Percentage cost reduction is calculated based on battery-only system.
Since the SC lifetime is nearly infinite, it is not considered in the annual operating cost
of the ESS in stand-alone PV power system. The Passive HESS reduces the battery cost
by 6.3% and 10.8% respectively for sunny and cloudy days, while both SC Semi-Active
HESS and Multi-level HESS demonstrate significant ESS cost reduction of about 43%
on a sunny day and 60% on a cloudy day. Despite the higher upfront battery cost (Lead-
acid and Lithium-ion) in Multi-level HESS, it only requires 20% of the SC capacity
compared to other HESSs.
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 119 -
5.5 Experiment verification
5.5.1 Testbed setup
To demonstrate the feasibility of the selected HESS topologies and to verify the
simulation analysis presented in the previous section, scale-down prototypes of stand-
alone PV-battery power system with the selected HESSs were designed and developed
as illustrated in Fig. 5.41. The test-bed is tested in campus of Swinburne University.
MPPT
Lead-acid Battery
Solar Irradiance
ipv
vpv
Charge Controller
Dpv
SC
SC
Ls
Cbus
Sw1 Sw2
ISC(ref)
EMS(Fig.5.11)
Sw1 Sw2
SC
Ls
Cbus
Sw1 Sw2
ISC(ref)
IBus
Li-ion
Ls
Cbus
Sw3 Sw4
EMS(Fig.5.16)
ILi-ion(ref)
Sw1 Sw2 Sw4Sw3
Pulse Load
IBus
IBus
DC/DC
InstalledPV Panel
EMS + HESS
SC Semi-active HESS
Multi-level HESS Passive HESS
Estimated load
0 6 12 18 00
0.5
1
1.5
2
2.5
3
Hours of Day
Pow
er (k
W)
Community HallTotal ConsumptionHousehold UseCommon Lighting
BK8500
Fig. 5.41 Experiment setup of selected HESS topologies
Inside the system, the Lead-acid battery is connected to the DC Bus through a charge
controller. The three HESS modules, marked with red dashed lines, can be individually
connected to the DC bus and tested. A programmable DC electronic load (BK Precision
BK8500) is used to emulate the pulsed load as well as the estimated load profiles. A
15W solar panel is used to generate the PV power. The current flows in energy storage
devices are measured by current sensors (ACS712) and logged by using the NI USB-
6008 data acquisition device. The power allocation algorithm is controlled by Arduino
(ATMEGA328P). The design and implementation of bidirectional buck-boost DC/DC
converter and its control system are presented in Appendix 2.1. The parameters of the
experiment testbed are summarized in Table 5.3.
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 120 -
Table 5.3 Experimental testbed parameters
System Parameters Passive HESS SC Semi-Active HESS Multi-level HESS
PV panel peak power 15W
Daily load energy consumption 0.4 kWh
Lead-acid battery nominal voltage 12V
Lead-acid battery capacity 30Ah
SC Capacitance - 50F 25F
SC Equivalent Series Resistance - 0.001Ω 0.001Ω
Lithium-ion Battery nominal voltage - - 12V
Lithium-ion Battery capacity - - 6Ah
5.5.2 Pulse load response
A repetitive pulsed current profile with amplitude of 1 Ampere, period of 120s, and 50
percent in duty ratio is generated by using BK8500. Figs. 5.42-5.44 show the responses
of battery and SC currents in each selected HESSs under pulse load test.
300 350 400 450
-0.5
0
0.5
1
1.5
Time (s)
Curr
ent (
A)
(a) LA Battery(b) SC(c) Pulse Load
Fig. 5.42 Experimental responses to pulsed load of Passive HESS
In Passive HESS (Fig. 5.42), the SC responded instantaneously to the step change in
current, while the battery picked up slowly with a time constant of about 1.5s. In SC
Semi-Active HESS, an Arduino controlled bi-directional buck/boost DC/DC converter
is used to control the current flow in SC module with a simple digital LPF to allocation
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 121 -
current among SC and battery modules. As can be seen from Fig. 5.43, the SC
responded quickly to the step change in current and allowed the battery to gently
supply/absorb the current change.
100 200 300 400
-1
-0.5
0
0.5
1
1.5
Time (s)
Cur
rent
(A)
(a) LA Battery(b) SC(c) Pulse Load
Fig. 5.43 Experimental responses to pulsed loads of SC Semi-Active HESS
800 900 1000 1100
-1
-0.5
0
0.5
1
1.5
2
Time (s)
Cur
rent
(A)
(a) LA Battery(b) Li-ion Battery(c) SC(d) Pulse Load
Fig. 5.44 Experimental responses to pulsed loads of Multi-level HESS
The current response of the Multi-level HESS is shown in Fig. 5.44. The structure
enables the primary battery to gently supply/absorb the changes but with notably lower
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 122 -
peak current because the Lithium-ion battery module shares part of the current demand
that can be determined by setting the scaling factor (set at 0.85 for this experiment). The
experimental results of pulsed load responses agree to the simulation results presented
in section 5.3.
5.5.3 Daily operation in stand-alone PV power system
The daily operational test with 15W stand-alone PV power system was carried out on
HESSs under test separately on four different partly cloudy days in Swinburne
University of Technology Sarawak Campus, Kuching, Malaysia. The net current demand
(𝐼𝑃𝑉 − 𝐼𝐿𝑜𝑎𝑑, black line), primary battery current (red line) and SC current (blue line) are
depicted in Figs. 5.45 – 5.48, respectively for battery-only system, system with Passive
HESS, system with SC Semi-Active HESS and system with Multi-level HESS.
0 4 8 12 16 20 0-1.5
-1
-0.5
0
0.5
1
1.5
Hours of Day
Curr
ent (
A)
(a) LA Battery (b) SC(c) PV-Load
Fig. 5.45 Experimental currents of battery-only in stand-alone PV power system
Minimal mitigation of current fluctuation is demonstrated in Passive HESS (Fig. 5.46),
while SC Semi-Active HESS and Multi-level HESS remove majority of the primary
battery current fluctuation as can be observed from Fig. 5.47 for SC Semi-Active HESS
and Fig. 5.48 for Multi-level HESS. In addition, the Multi-level HESS shares part of the
current demand with Lithium-ion battery module with a pre-determined scaling factor.
The experimental results demonstrate the feasibility of the HESS under test in stand-
alone PV power system and validate the simulation analysis presented in Section 5.4.2.
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 123 -
0 4 8 12 16 20 0-1.5
-1
-0.5
0
0.5
1
1.5
Hours of Day
Curr
ent (
A)
(a) LA Battery (b) SC(c) PV-Load
Fig. 5.46 Experimental currents of Passive HESS in stand-alone PV power system
0 4 8 12 16 20 0-1.5
-1
-0.5
0
0.5
1
1.5
Hours of Day
Cur
rent
(A)
(a) LA Battery(b) SC(c) PV-Load
Fig. 5.47 Experimental currents of Semi-Active HESS in stand-alone PV power system
Chapter 5 Battery-SC HESS for Stand-alone PV Power System in Rural Electrification
- 124 -
0 4 8 12 16 20 0-1.5
-1
-0.5
0
0.5
1
1.5
Hours of Day
Curr
ent (
A)
(a) LA Battery(b) Li-ion Battery(c) SC(d) PV-Load
Fig. 5.48 Experimental currents of Multi-level HESS in stand-alone PV power system
5.6 Conclusion
Stand-alone PV power system with Lead-acid battery has been one of the preferred
choices in off-grid rural electrification. However, the nature of solar energy is causing
the additional impact on the battery which accelerates the deterioration of battery
performance and cycle life. This chapter presented a comprehensive study of Battery-
SC HESS and their feasibility in stand-alone PV power system. Three potential HESS
topologies and their associated power allocation strategy, and control system had been
discussed in this chapter, followed by numerical simulation and experimental
verification. The Matlab Simulink models of the selected HESSs were developed and
simulated with actual solar irradiance data and estimated load profile to evaluate the
effectiveness in mitigating battery stress. The simulation analysis and results had been
verified by experiments with the developed lab-scale prototype of HESS under
consideration. Simulation results, battery health cost and financial analyses, and
empirical outcomes suggest that the combination of active secondary energy storage
with the passive primary battery could be the optimal setting for stand-alone PV power
system applications.
- 125 -
Chapter 6
Smart HESS Plug-in Module for Stand-
alone PV-Battery Power System
6.1 Introduction
The structure of stand-alone PV power system, illustrated in Fig. 6.1, consists of PV
arrays, charge controller, inverter, the Lead-acid battery, and AC/DC loads. This
conventional stand-alone PV-battery power system has been widely installed in off-grid
rural communities. Chapter 5 discussed and compared three HESS topologies that are
suitable for stand-alone PV power system and the technical analysis and simulation
outcomes showed that the proposed Multi-level HESS could effectively mitigate battery
stress and thus leading to enhanced lifetime characteristic of the Lead-acid battery bank.
However, to achieve the Multi-level Battery-SC HESS as demonstrated in Chapter 5, a
complete redesign of the existing installed ESS structure is required. This may not be
financially viable in most cases, especially in remote applications.
Fig. 6.1 The stand-alone PV power system with Lead-acid battery
Lead-acid Battery
Charge Controller
Inverter AC Load
DC LoadDC/DC(MPPT)
Plug-inModule
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 126 -
Typical stand-alone PV-battery power system consists of PV arrays, charge controller,
inverter, ESS and loads. Typical solar charge controller features MPPT that maximizes
the power generation, and regulates the battery charging process by monitoring the
battery SoC to prevent overcharging and overly discharged [284]–[286]. However, other
life-limiting factors that accelerate the deterioration of battery performance such as high
C-rate, fluctuating power exchange, frequent charge-discharge transition, deep-
discharging, and other external factors are often not considered in the research of the
charge controllers [287]–[289].
In this chapter, a novel Smart Hybrid Energy Storage System (SHESS) plug-in module is
proposed that is retrofittable on typical stand-alone PV-battery power systems, as shown
in Fig. 6.1. The proposed module is designed as a plug-in that can be adopted directly in
existing installed infrastructure in the installed stand-alone PV-battery power system. By
design, it mitigates the principal Lead-acid battery operation stress from current
fluctuations and surge demand without changing the structure of the original system.
Such a scheme is simple, effective and will have a significant economic impact on the
market of the installed PV system.
The proposed SHESS plug-in module consists of SC and Lithium-ion battery modules
that operate in two different modes based on weather conditions: (1) light mode for
operation under sunny day condition and (2) heavy mode for operation under cloudy day
condition. The performance metric of the three energy storage technologies is tabulated
in Table 6.1 [176], [290], [291].
Table 6.1 Comparison of energy storage technologies in SHESS
Lead-acid Battery SC Lithium-ion Battery
Specific Energy Density 30 -50 Wh/kg 0.1 – 15 Wh/kg 100 - 250 Wh/kg
Specific Power Density 75 - 300 W/kg 500-15,000 W/kg 230– 340 W/kg
Life Cycle 500-1000 100,000+ 1,000-20,000
Charge/Discharge Efficiency 80 – 90 % >90% >90%
Shortest Response Time 1 min 0.1 – 1 s 30 s
Self-Discharge/ Day 0.1-0.3% 20-40% 0.1-0.3%
Unit Cost ($/kWh) 300 2000 500
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 127 -
In sunny day condition, PV power is relatively stable for which only SC module will be
activated (light mode) to complement the battery operation. In light mode, the SC will be
interfaced to battery terminal by using a bidirectional DC/DC converter that is actively
controlled by the microcontroller. While in cloudy day condition, the PV generates less
power and fluctuates more frequently. Therefore, the heavy mode will be activated
where an additional Lithium-ion battery module is activated to provide the required
capacity in absorbing the current fluctuation. The current exchange will be decomposed
into three frequency components (high, middle and low) and allocated reasonably to the
SHESS plug-in modules of different lifetime characteristics (SC and Lithium-ion) and
the primary Lead-acid battery bank.
Computational model of the proposed SHESS plug-in module is developed and
evaluated in Matlab Simulink. Dynamic modelling and numerical simulations are carried
out to examine the effectiveness of the SHESS plug-in module in mitigating battery
stresses under different operating conditions. A scaled-down prototype of the proposed
SHESS plug-in module is examined experimentally to verify the simulation outcomes
and demonstrate the feasibility of the proposed system. To evaluate the technical and
financial improvements of the stand-alone PV power system with SHESS, a financial
analysis is presented by quantitatively investigating the lifetime improvement with
battery health cost model proposed in Chapter 5.
6.2 SHESS Plug-in module
6.2.1 System structure
The structure of the proposed SHESS plug-in module is illustrated in Fig. 6.2. The
SHESS is connected to the terminal of the Lead-acid battery. A mode controller
interfacing the Lead-acid battery and the SHESS plug-in module is implemented to
control the mode of operation. In light mode, only the SC module is interfaced to the
Lead-acid battery terminal via an actively controlled bidirectional DC/DC converter. The
active connection ensures DC bus stability while allowing the SC to operate in a wide
range of terminal voltages. In this mode, high-frequency current fluctuation will be
directed to the SC module that is controlled by the power allocator.
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 128 -
Differently, both SC and Lithium-ion modules will be activated in heavy mode, where
both SC and Lithium-ion modules are interfaced with actively controlled bidirectional
DC/DC converters. This configuration will ensure sufficient capacity in handling severe
fluctuation in current without requiring a large amount of costly SC to be installed. In
this setting, the SC module will absorb/supply the high-frequency current fluctuation,
while the Lithium-ion module is controlled to absorb/supply the medium frequency
component of the fluctuating current, and at the same time to supply a portion of the total
power demand. A power-sharing factor W1 determines the proportion of power-sharing
within the power allocator. The power allocator adopts the low pass filtering approach in
decomposing the power demand into multiple frequency components. A power
controller is used to coordinate the operation of mode controller and power allocator
while generating appropriate PWM signals to operate the individual bidirectional DC/DC
converters.
Fig. 6.2 SHESS plug-in module in stand-alone PV-battery power system
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 129 -
6.2.2 Power allocation and control strategy
The signal of power difference is collected and process via the central control system
that contains Power Allocation Controller (PAC) and Energy Management Unit (EMU).
The EMU is used to process the signals, determine the corresponding operating mode,
and send the signal to the PAC, as well as the DC/DC converters and Mode controller.
According to different working modes, the system will divide the signal into different
frequency parts and send it to the control unit. Fig. 6.3 shows the mode selection process
when the SHESS is operational. The mode controller can be configured as the automatic
mode or manual mode. In automatic mode, the selection of mode will be made
automatically based on real-time or predicted (from solar irradiance data) weather
conditions. While in manual mode, the operating mode will be manually set by the user.
This simple method will be attractive for the applications in remote areas.
Solar Irradiance
Manual setup
WeatherConditions
Sunny
Cloudy
Plug-in/off
Mode Selection
SC Li-ion
Off Mode(LA-Only) Off Off
Light Mode(Sunny) On Off
Heavy Mode(Cloudy) On On
Controller signal
Automatic setup
Fig. 6.3 Mode selection process of the proposed SHESS plug-in module
There are three modes of operation, namely off mode, light mode and heavy mode. In
light mode, SC module will be configured to respond actively to the high-frequency
power exchange while the average power demand (low-frequency components) will be
supplied passively by the primary Lead-acid battery. In the heavy mode, both the
Lithium-ion battery module and SC module will be parallel connected to the Lead-acid
battery. The power demand will be decomposed into three frequency components, (1)
high-frequency, (2) intermediate frequency, and (3) low-frequency. The high-frequency
power exchange will be responded by the SC module, while the Lithium-ion battery
module will cover the intermediate frequency, and lastly, the average power demand
(low-frequency) will be powered by the primary Lead-acid battery passively.
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 130 -
Heavy Mode
Ppv
Pload
+-
PESS
LPF (Primary)
+ -
+-
PSC (ref)
LPF (Secondary)
W1
PLi-ion (ref)
(a) Power Allocator for SHESS
PSC(ref) 1/VSCISC(ref)
PI PWMD+
-
ISC
Switching Signal(SC Converter)
PLi-ion(ref) 1/VLi-ionILi-ion (ref)
PI PWMD+
-
ILi-ion
Switching Signal (Li-ion Converter)
(b) Linearized Model of the Li-ion and SC Current Control Loop
Mode Control
Light Mode
Fig. 6.4 Power allocation strategy for the SHESS plug-in mode
(1) Light mode
In the light mode, the power allocation strategy is shown in Fig. 6.4(a). High-frequency
component PSC(ref) is extracted from the net demand power PESS (PPV - Pload) using the
secondary LPF. The SC actively handles the high-frequency components, and the battery
responsible for the low-frequency ones in a passively way. The signal of PSC(ref) will be
the input reference signal for the controller to generate appropriate PWM signals that
operates the bidirectional DC/DC converter for the SC module as shown in Fig. 6.4(b).
While the remaining smoothed power demand (low-frequency component) will be
supplied by the passively connected Lead-acid battery.
(2) Heavy mode
In the heavy mode, the SHESS utilizes two LPFs to decompose the power demand into
three different frequency components as shown in Fig. 6.4(a). The highest frequency
component PSC(ref) will be supplied by the SC module. While the middle frequency
component PLithium-ion(ref) will be covered by the Lithium-ion battery module. A weight
factor W1 is implemented to set the load proportion of Lithium-ion battery module with
reference to the total power demand PESS. In this way, the load of the Lithium-ion battery
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 131 -
module can be flexibly adjusted according to the installed capacity, to achieve optimal
power-sharing among different modules. Moreover, the W1 can be set manually or
modified dynamically by advanced control algorithms to satisfy different operating
conditions. In Fig. 6.4(b), it depicts the control systems for generating appropriate PWM
signals to operate bidirectional DC/DC converters of both SC and Lithium-ion battery
modules. Finally, the original Lead-acid battery passively absorbs/supplies the low-
frequency currents.
In addition to the hybrid integration of the Lead-acid battery and SHESS, it is also
critical to determine the cutoff frequency of LPF in both operation modes. In practice,
the cut-off frequency needs to be carefully considered based on the capacity of the Lead-
acid battery itself and the installed capacity of the SHESS. The cut-off frequencies
determine the smoothness of the fluctuating current in the Lead-acid battery and can be
calculated in real-time using advanced algorithms, or be manually adjusted by preset
optimization values. Researchers have made considerable efforts to optimize cutoff
frequency determination to maximize the benefits of HESS. The main research of this
chapter is to propose the SHESS plug-in module that can extend the lifetime of the main
battery in the installed PV system, and use simulation test and experimental verification
to demonstrate its operating characteristics and verify its feasibility. Therefore, the
algorithms for the mode selection, cut-off frequency determination, and the dynamic
adjustment of weight factor will not be discussed in details in the following subsections.
6.3 Simulation analysis
In this subsection, the Matlab Simulink model and simulation results of the proposed
SHESS plug-in module are presented. The model is tested with standard pulsed load and
actual PV-battery PV system operational.
6.3.1 Pulse load response
The pulsed load used in simulation has a period of 10s and 5A of amplitude with a fixed
50% duty cycle. In light mode, only the SC module is activated to absorb the fluctuating
current. While in heavy mode, both the SC module and Lithium-ion battery module are
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 132 -
activated to perform power-sharing. Fig. 6.5 shows the SHESS model developed in
Matlab Simulink for pulse load test. Two switch breakers are implemented to simulate
the mode controller. The EMS simulates real-time power allocation and control
algorithms. The capacity of Lead-acid Battery and Li-ion Battery is set at 300Ah (12V) and
15Ah (12V), respectively. While the installed capacitance of SC is 50F.
Fig. 6.5 Matlab Simulink model of SHESS used in pulse load testing
(1) Light mode
Fig. 6.6 shows the simulation result for power-sharing between the Lead-acid battery and
the SC module under pulsed current load. During step change in current (from 0A to 5A),
the SC module is activated and discharges rapidly to fulfill the sudden change in current,
while the Lead-acid battery discharges gradually towards the current demand. In the OFF
state (from 5A to 0A), the SC module absorbs the excess current and gradually reduces
the Lead-acid battery current towards zero. Throughout the process, the battery can be
slowly discharged and charged at its own rate. The sum of the charge and discharge from
the two energy storage elements is equal to the value of the pulse load.
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 133 -
15 20 25 30 35 40 45 50-6
-4
-2
0
2
4
6
8
10
Time (s)
Cur
rent
(A)
LA BatterySCPulse Load
SC ModuleActivated
Fig. 6.6 Simulated results in pulse load testing in light mode
(2) Heavy mode
On the other hand, both of the SC module and Lithium-ion battery module are parallel
connected (both switch breakers are activated) with Lead-acid battery terminal in heavy
mode. Fig. 6.7 depicts the current profiles for Lead-acid battery, Lithium-ion battery
module, and SC module under pulsed current load.
0 5 10 15 20 25 30 35 40 50-6
-4
-2
0
2
4
6
8
10
Time (s)
Cur
rent
(A)
Li-ion BatteryLA BatteryPulse LoadSC
SC/Li-ion HESSModule Activated
Fig. 6.7 Simulated results in pulse load testing in heavy mode
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 134 -
The pulsed current was split into three frequency components, where the SC module
responded quickly to step change, while the Lithium-ion battery module took a small
portion of the overall capacity and at the same time responded to the middle frequency
component. As can be observed from the figure, the peak current of the Lead-acid
battery is reduced due to the W1 factor where the Lithium-ion battery module supplies a
small portion of the current demand.
6.3.2 Operation in stand-alone PV-battery power system
Fig. 6.8 illustrates the Matlab Simulink model of the SHESS plug-in module integrated
into a five kilowatts stand-alone PV-battery power system. The system model contains
5kW (peak) PV arrays, 4000Ah Lead-acid battery with 12V rated voltage, AC/DC loads,
and SHESS plug-in module interfaced with two individual bidirectional buck-boost
DC/DC converters. In SHESS plug-in module, the initial weight factor is set as 0.95, and
the installed Lithium-ion battery module is 200Ah with 12V rated voltage. The SC
capacitance is 100F. The simulations are conducted under the same daily solar irradiance
data profiles of the sunny and cloudy days as shown in Figs.5.17 and 5.18 (Chapter 5)
and the estimated load profile as presented in Fig. 5.19 (Chapter 5).
Fig. 6.8 Matlab Simulink model of stand-alone PV power system with SHESS
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 135 -
Multi-level LPFs are used to perform power decomposition in different operating modes.
In light mode, the power allocator generates reference signal PSC(ref) for the controller to
generate PWM signal to execute the SC module. The LPF time constant is set to 300s. In
the heavy mode, the power allocator splits the power demand PESS into reference signals
for Lithium-ion battery module PLithium-ion(ref) and SC module PSC(ref) by using Multi-level
LPFs (as shown in Fig.6.4(a)) with time constants of 600s and 300s, respectively. In both
operating modes, the Lead-acid battery responds passively to the remaining power
demand (low-frequency component).
(1) Retrofittability test
To examine the retrofittable feature of the SHESS plug-in module on the typical stand-
alone PV-battery power system, the SHESS was activated halfway during the 24-hour
simulation for both operating modes. Figs. 6.9 and 6.10 illustrate the 24-hour simulation
results of SHESS plug-in module light mode (Fig. 6.9) and heavy mode (Fig. 6.10).
In both modes, the PV-battery power system operated without the SHESS plug-in
module during the first half of the simulation time. The SHESS plug-in module was
activated at 12:00 PM to perform the power-sharing for the second half of the simulation
time. The plug-in action occurs at around 12:00 PM, the Lead-acid battery continuously
starts to run with a smooth current curve, and the negative impact of the peak current is
significantly diminished. The SHESS can adequately compensate the rapid current
variation either from PV generation or load demand. When the power demand is positive
(Pload > PPV), the SHESS plug-in module supplies power to the DC bus, while the
SHESS plug-in module absorbs excess power from the DC bus when the power demand
is negative (Pload < PPV).
It can be observed that the Lead-acid battery current (red line) absorbs all the current
fluctuations due to intermittent PV power without the SHESS (first half of simulation
time), whereas the Lead-acid battery current is significantly smoothed after the SHESS
was activated (second half of simulation time). The SC current (blue line) responded
effectively to absorb/supply the high-frequency current. In the light mode, the SC current
varies from -20A to 20A, which covers the fastest current fluctuations and is sufficient to
smooth the Lead-acid battery operating current profile. In the heavy mode, Lithium-ion
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 136 -
battery is utilized to mitigate power fluctuations in the middle frequency range and
extend the SC current range to -50A to 50A. The Lead-acid battery still can operate
under a smooth current curve. It is noted that the SC needs to reduce the current variation
from approximately -80A to 80A without the integration of Lithium-ion battery module.
This means that larger SC capacity is required, leading to a substantial increase in cost.
0 4 8 12 16 20 0-100
-60
-20
20
60
100
Hours of Day
Cur
rent
(A)
(a) PV-Load(b) LA Battery(c) SC
SC Module Activatied
Fig. 6.9 Simulation results of plug-in testing in light mode
0 4 8 12 16 20 0-80
-40
0
40
80
Hours of Day
Cur
rent
(A)
(a) PV-Load(b) LA Battery(c) Li-ion Battery(d) SC
SC/Li-ion HESSModule Activated
Fig. 6.10 Simulation results of plug-in testing in heavy mode
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 137 -
(2) SHESS under 24-hour operation
The results in retrofittability test presented above demonstrate integrateability of the
proposed SHESS to the existing PV system and the capability to effectively reduce the
current fluctuations of the primary Lead-acid battery. To further evaluate the
performance of SHESS plug-in module in mitigating battery stresses under continuous
operation, a daily PV-battery power system operation was simulated for both modes. The
SHESS model parameters (PV and Lead-acid battery capacity) and simulation conditions
(solar irradiance and load profile) were set identical. Figs. 6.11 and 6.12 show the daily
Lead-acid battery current profiles under light mode (Fig. 6.11) and heavy mode (Fig.
6.12). It can be observed that the Lead-acid battery current profiles under both operating
modes have been significantly smoothed with the SHESS plug-in module installed.
4 8 12 16 20
-60
-20
20
60
100
0 4 8 12 16 20 0
-80
-40
0
40
80
Hours of Day
Cur
rent
(A)
(a) PV- Load(b) LA Battery
With SC Module
Without SC Module
Fig. 6.11 Lead-acid battery currents profile in light mode
On cloudy days, the solar irradiance changes too violently which requires enormous SC
capacity to effectively mitigate the severe current fluctuations, if SC-only HESS is
implemented. In order to balance the smoothness of the Lead-acid battery current and the
overall system cost, the capacity of the SHESS has to be designed to make the Lead-acid
battery operates with a relatively smooth curve instead of a remarkably smooth curve.
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 138 -
This is also why the SC/Lithium-ion HESS mode was introduced under cloudy
conditions to replace the SC-only mode. As an inexpensive ESS technology compared to
SC, the Lithium-ion battery absorbs/supplies a part of the high-frequency components in
the overall demand power and corporate with SC to maximally remove the Lead-acid
battery current fluctuations. This approach effectively extends the lifetime of the Lead-
acid battery while also ensures that the system is maintained at a lower cost range.
4 8 12 16 20
-60
-20
20
60
100
0 4 8 12 16 20 0-80
-40
0
40
80
Hours of Day
Cur
rent
(A)
(a) PV- Load(b) LA Battery
With SC/Li-ion HESS Module
Without SC/Li-ion HESS Module
Fig. 6.12 Lead-acid battery currents profile in heavy mode
(3) Battery healthy cost analysis
Insert the simulation results to the battery health cost function Cost(T) which was
presented as Eq.(5.32) in Chapter 5, Figs. 6.13 and 6.14 show the normalized cumulative
battery health cost in light mode (Fig. 6.13) and heavy modes (Fig. 6.14) respectively. In
sunny day condition, the simulation results show that the SHESS plug-in module under
light mode reduces the battery health cost by 26.2% compared to the Lead-acid battery-
only system. In the case of cloudy day condition, the SHESS under heavy mode achieved
the battery health cost of about 43.8% reduction compared to battery-only settings.
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 139 -
0 4 8 12 16 20 0
0.4
0.6
0.8
1
Hours of Day
Cos
t (T)
(a) LA Battery-Only(b) With SC Module
Max : 1.000
Max : 0.738
Fig. 6.13 Normalised cumulative battery health cost in light mode
0 4 8 12 16 20 00.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
Hours of Day
Cos
t (T)
(a) LA Battery-Only(b) With SC/Li-ion HESS Module Max : 1.830
Max : 0.806
Fig. 6.14 Normalised cumulative battery health cost in heavy mode
Based on the battery health cost analysis presented above, a financial analysis is
presented in Table 6.2 to estimate the annual operating cost improvement with SHESS
plug-in module installed. The analysis assumes that the LA battery’s life cycle is linearly
proportional to the reciprocal of battery health cost. Based on the energy storage review
in [85] [106], the estimated life cycle of battery for different topologies are calculated
based on the typical life expectancy of 500 cycles for LA battery and 4000 cycles for Li-
ion battery. In [135][292], the power capacity cost of LA battery is around 150 ~ 500
$/kWh and the Li-ion battery is around 600 ~ 2500 $/kWh for small-scale power system.
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 140 -
The Li-ion battery is estimated to perform 50% of the expected cycle life under
fluctuating current condition. Assuming the LA battery is cycled once a day within the
entire year, the estimated cost per cycle is calculated. The capacity of SC module in both
light and heavy modes is set identical. Due to the extremely long service life of the SC,
normally higher than 100,000 times, this paper neglects the performance deterioration of
SC and assumes infinite lifetime in the economic analysis. Under these assumptions,
25.4%~25.8% annual operating cost reduction is projected under sunny day conditions,
while a higher 52.4%~52.7% cost reduction is estimated under highly dynamic power
fluctuation on cloudy condition.
Table 6.2 Financial analysis of SHESS under different modes
Operation mode Weather condition
Battery Capacity
(kWh)
Initial Cost1
($) Cost(T)
2
Estimated Life Cycle
3
Cost / Cycle ($)
Estimated Annual
Battery Cost ($)
Cost Reduction
4
(%)
Battery-only Sunny 48 (LA)
5 7200~24000 1.000 500 14.4~48.0 5256~17520 0
Cloudy 48 (LA) 7200~24000 1.830 273 26.3~87.9 9600~32084 0
Light Mode (with SC) Sunny 48 (LA) 7200~24000 0.738 677 10.6~35.5
(3869~12958) + 50 (SC)
6
25.4 ~ 25.8%
Heavy Mode (with SC/Li-ion) Cloudy
48 (LA) 7200~24000 0.806 620 11.6~38.7 (4490~15221) + 50 (SC)
6
52.4~52.7% 2.4 (Li-ion) 1440~6000 - 2000
3 0.7~3.0
#Note 1 – Initial cost of Lead-acid battery ($256/kWh) and Lithium-ion battery ($290/kWh) are considered.[269] #Note 2 – Typical life cycle / Cost of battery utilization; (typical life cycle for Lead-acid – 500 cycles, Li-ion – 4000 cycles and SC >100,000 cycles)[269] #Note 3 – Estimated to perform 50% of the expected lifecycles of the Li-ion battery when LA battery is replaced; #Note 4 – Percentage cost reduction is calculated based on battery-only system; #Note 5 – Assume the LA Battery: 4000 Ah with 12 volts; Li-ion Battery: 200Ah with 12 Volts (Weight factor: 0.5); #Note 6 – Cost of 500F SC is around $50 https://item.taobao.com/item.htm?ft=t&spm=a21m2.8958473.0.0.668e3663aIH9be&id=529538036640,
6.4 Experiment verification
Fig. 6.15 Prototype of the SHESS plug-in module
DC/DC for SC
DC/DC for Li-ionMicroprocessor
Supercapacitor Current sensors
NI USB-6008 data acquisition Li-ion Battery
Primary Lead-acid Battery
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 141 -
In order to evaluate the viability of the proposed SHESS plug-in module in retrofitting
the typical Lead-acid battery-only stand-alone PV power system, a down-scaled
prototype, as shown in Fig. 6.15, has been developed and tested in laboratory settings.
Experiments were carried out to examine the pulsed load response and operation in
scaled stand-alone PV-battery power system. The parameters of main components are
summarized in Table 6.3. The currents of the Lead-acid battery and SC and Lithium-ion
battery were measured and recorded using current sensors (ACS712) and microcontroller
(ATMEGA328P).
Table 6.3 Experiment testbed parameters
Parameters Lead-acid Only Light Mode Heavy Mode
PV panel peak power 15W
Daily load energy consumption 0.4 kWh
Lead-acid Battery nominal voltage 12V
Lead-acid Battery capacity 30Ah
SC Capacitance - 25F
SC Equivalent Series Resistance - 0.001Ω
Lithium-ion Battery nominal voltage - - 12V
Lithium-ion Battery capacity - - 2Ah
6.4.1 Pulse load response
Fig. 6.16 depicts the experimental setup and circuit diagram for pulsed load response.
Two bidirectional buck-boost DC/DC converters interfacing SC and Lithium-ion battery
modules are implemented and parallel connected with the Lead-acid battery through DC
bus. The periodic pulsed load is generated using a programmable DC electronic load
(BK Precision BK8500). The period, amplitude and duty ratio of the pulsed load are set
to 120s, 1 ampere, and 50%, respectively. The EMS uses the strategies in Figs. 6.3 and
6.4 which determine the operation mode, plug-in status and controls the signals to the
DC/DC converters in SHESS plug-in module. The testing is executed in the campus of
Swinburne University, Sarawak, Malaysia.
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 142 -
Fig. 6.16 Experimental setup and circuit diagram for the pulse load testing
Figs. 6.17 and 6.18 show the pulsed load responses of SHESS plug-in module under
light mode (Fig. 6.17) and heavy mode (Fig. 6.18). In light mode (Fig. 6.17), the SC
current responses rapidly to supply the step change in load, while the Lead-acid battery
current responses gradually towards the demanded current.
100 200 300 400
-1
-0.5
0
0.5
1
1.5
2
Time (s)
Cur
rent
(A)
(a) LA Battery(b) SC(c) Pulse Load
SC Module Activatied
Fig. 6.17 Experiment results of the pulse load testing (light mode)
Lead-acid Battery
SC
Pulse Load
Ls
Cbus
Sw1 Sw2Plug-in Control
ISC(ref)
IBatt
Li-ion
Ls
Cbus
Sw3 Sw4Mode
Control
EMS(Figs.6.3~6.4)
ILi-ion(ref)
Sw1 Sw2 Sw4Sw3
Plug-in Control
ModeControl
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 143 -
In heavy mode (Fig. 6.18), the SC picked up the step current load as expected, while the
Lithium-ion battery module supplies a portion of the remaining load demand. The Lead-
acid battery current responses gradually and a portion of the demanded current is shared
the Lithium-ion battery module. Thus, the experimental results of the pulse load response
demonstrate the power-sharing capability of the SHESS plug-in module and verify the
simulation outcomes as presented in Figs. 6.6 and 6.7.
700 800 900 1000 1100
-1
-0.5
0
0.5
1
1.5
2
Time (s)
Curr
ent (
A)
(a) LA Battery(b) Li-ion Battery(c) SC(d) Pulse Load
SC/Li-ion HESSModule Activated
Fig. 6.18 Experiment results of the pulse load testing (heavy mode)
6.4.2 Operation in the lab-scale stand-alone PV-battery power system
To further verify the feasibility of the SHESS plug-in module, a down-scaled stand-alone
PV-battery power system with SHESS plug-in module prototype was developed and
tested under actual operating conditions. The experimental setup is shown in Fig. 6.19.
The PV-battery power system includes a 15Wp PV panel, a charge controller with MPPT,
a 12V 30Ah Lead-acid battery, and a programmable DC electronic load to emulate the
load profile. The charge controller is kept connected the PV panels and Lead-acid
battery by default. The plug-in module with two buck/boost DC/DC converters is
connected, and EMS controls the operation mode according to the weather conditions.
The currents of the PV panel, load, Lead-acid battery, SC and Lithium-ion battery were
measured and logged by using the NI USB-6008 data acquisition device for 24-hours.
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 144 -
Fig. 6.19 Experimental setup and circuit diagram for the case study
The experiment was carried out on five different days in Swinburne University (Sarawak
Campus), Kuching, Malaysia, one day for battery only testing, two days for plug-in
testing and two more days for one-day testing.
0 4 8 12 16 20 0-1.5
-1
-0.5
0
0.5
1
1.5
Hours of Day
Curr
ent (
A)
(a) LA Battery(b) Plug-in Module(c) PV-Load
Fig. 6.20 Experiment results of the stand-alone PV-battery power system
MPPT
Lead-acid Battery AC Loads
Solar Irradiance
ipv
vpv
Charge Controller
Dpv
SC
Ls
Cbus
Sw1 Sw2
Plug-in Control
ISC(ref)
IBatt
Li-ion
Ls
Cbus
Sw3 Sw4Mode
Control
EMS(Figs.6.3~6.4)
ILi-ion(ref)
Sw1 Sw2 Sw4Sw3
inverter
DC Loads
Plug-in Control
Mode Control
Weather Condition
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 145 -
As a reference, the stand-alone PV-battery power system is operated independently in 24
hours in a partly cloudy day. The Lead-acid battery current profile and power demand
PPV-Load are illustrated in Fig. 6.20, and solar irradiance is available from 8:00 AM- 17:00
PM It is seen that high transient currents, varies from ± 1.5A, are drawn from the Lead-
acid battery, which considerably reduces lifetime.
(1) Retrofittability test
In order to demonstrate the ease of being retrofit on existing installed PV-battery power
system, the SHESS plug-in module was activated at 12 PM during the experiment. Figs.
6.21 and 6.22 show the current profiles of the Lead-acid battery and SHESS plug-in
module. It is noted that the power-sharing process is initiated when the SHESS plug-in
module was activated after 12 pm, and the Lead-acid battery current is significantly less
current fluctuation. In the sunny day (Fig. 6.21), the SHESS plug-in module operated
under light mode with SC current fluctuated between -0.5A to 1A. The SC module
responded to the fluctuating current between 12 PM to 3 PM, while remain inactivated
when the current demand was relatively stable during night time.
0 4 8 12 16 20 0-1.5
-1
-0.5
0
0.5
1
1.5
Hours of Day
Cur
rent
(A)
(a) LA Battery(b) SC(c) PV-Load
SC Module Activatied
Fig. 6.21 Experimental plug-in testing of SHESS plug-in module (light mode)
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 146 -
On the cloudy day, as shown in Fig. 6.22, the current demand (IPV - ILoad) varied heavily
with rich harmonic. Despite the massive current fluctuation, the SC maintained a current
variation of within 1A, while the Lithium-ion battery module shared part of the
intermediate frequency current fluctuation. This allows the SHESS plug-in module to
perform equally well with the same SC capacity installed. In addition, the Lithium-ion
battery module shared 5% of total power demand with the weight factor W1 set to 0.95,
which reduces the C-rate of the Lead-acid battery. The experimental results show that the
SHESS plug-in module can reduce the Lead-acid battery stress through properly
controlled power allocation.
0 4 8 12 16 20 0-1.5
-1
-0.5
0
0.5
1
1.5
Hours of Day
Cur
rent
(A)
(a) LA Battery(b) Li-ion Battery(c) SC(d) PV-Load
SC/Li-ion HESSModule Activated
Fig. 6.22 Experimental plug-in testing of SHESS plug-in module (heavy mode)
(2) Daily operation in stand-alone PV-battery power system
The SHESS plug-in module is tested while connecting to the DC bus by running 24
hours in both operations, sunny and cloudy, as shown in Figs. 6.23 and 6.24 respectively.
With the integration of the SHESS plug-in module, the Lead-acid battery current
fluctuations are suppressed noticeably in both weather scenarios. In Fig. 6.23, SC
module absorbed most of the high peak currents variations in a range of -0.5 A to 1A. In
Fig. 6.24, the solar irradiance varies much heavy than in sunny mode and leads more
power demand fluctuations with rich surge peak current components. The Lithium-ion
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 147 -
battery shared a portion of total power demand in a moderate variation frequency, and
the SC still operated in the same range as in sunny mode. Accordingly, it is evident that
the SHESS plug-in module works appropriately and efficiently releases the Lead-acid
battery operate stress all over the day.
0 4 8 12 16 20 0-1.5
-1
-0.5
0
0.5
1
1.5
Hours of Day
Cur
rent
(A)
(a) LA Battery(b) SC(c) PV-Load
Fig. 6.23 Experimental one day testing of SHESS plug-in module (light mode)
0 4 8 12 16 20 0-1.5
-1
-0.5
0
0.5
1
1.5
Hours of Day
Cur
rent
(A)
(a) LA Battery(b) Li-ion Battery(c) SC(d) PV-Load
Fig. 6.24 Experimental one day testing of SHESS plug-in module (heavy mode)
Chapter 6 Smart HESS Plug-in Module for Stand-alone PV-Battery Power System
- 148 -
6.5 Conclusion
Typical stand-alone PV power systems with the Lead-acid battery are widely installed in
remote areas. Typical charge controllers lack the considerations the life-limiting factors
of the battery such as C-rate, DoD and current fluctuations, which are commonly
encountered in stand-alone power systems. This chapter proposed a SHESS plug-in
module that is retrofittable to existing installed PV-battery power systems to mitigate
battery stress by absorbing the damaging current profile. Two operation modes are
designed to face the sunny and cloudy weather conditions. Matlab Simulink model of the
SHESS plug-in module has been developed and simulated to investigate the power-
sharing capability. Battery health cost analysis is presented to qualitatively evaluate the
improvement in battery health and reduction in system operating cost. The analysis
shows that after installing the SHESS plug-in module, the annual operating cost can be
reduced up to 53.7%. A lab-scale prototype of the SHESS plug-in HESS was constructed
and tested under the same lab-scaled stand-alone PV-battery power system in Chapter 3,
including the pulse load test, plug in/off test, and one-day test. The experiment results
demonstrated the ease of being integrated into existing installed PV-battery power
system and were in good agreement with the simulation results.
- 149 -
Chapter 7
Conclusion and Future Work
7.1 Summary
Energy storage technology provides a way to increase grid flexibility and enable the
integration of intermittent, non-distributable renewable power generations. In Chapter
2, an overview of the state-of-the-art in energy storage technologies was presented,
including CAES, FES, PHS SC, SMES, cell battery, flow battery, TES, and chemical
energy storage. Their operation principles, technical performance, and economic aspects
and the current research and development status were discussed, classified, compared
and analyzed. Following this, a comprehensive comparison and potential applications
analysis of the reviewed technologies were presented systematically to illustrate the
advantages and limitations of various energy storage technologies in the view of
different perspectives. Selection criteria and consideration that intends to help decision
makers and researchers to select suitable energy storage technologies in specific
applications was presented. The future development trend of different energy storage
technologies was discussed.
The PV-based power system is seen to be a promising renewable energy technology in
the off-grid applications in remote areas. Chapter 3 presents an introduction of solar
cells and the core components in a typical PV power system. The design methodology,
including site evaluation, solar irradiance measurement, load profile estimation, and
system analysis were presented. Based on the collected data of solar irradiance and the
estimated load profile, dynamic modelling and simulation of a stand-alone PV-battery
power system were conducted in Matlab Simulink. The results show the typical
Chapter 7 Conclusion and Future Work
- 150 -
behaviour of the battery charge-discharge process under off-grid operation. With actual
data of solar irradiance and estimated load profiles, the battery current is demonstrated
to behave under severely fluctuating conditions, which tends to accelerate the
performance deterioration and aging process of the Lead-acid battery bank.
Hybridization of battery and supercapacitor has been reported to be one of the effective
ways to mitigate the operational stress on the Lead-acid battery, leading to enhanced
lifetime characteristics. Energy storage elements of different electrical and lifetime
characteristics complement each other up and down during the operation and thus
optimize the operation and longevity. Chapter 4 reviews different HESSs, including the
system topology, control strategies, and the associated energy management system.
Their corresponding characteristics, advantages, disadvantages and possible
applications in stand-alone PV power system were discussed and compared.
A feasibility study is presented in Chapter 5 and HESS topologies, and associated
power allocation strategy that is practically applied to remote microgrid were identified,
considering their system complexity, technical merits, and limitations. Theoretical
analysis and numerical simulation in Matlab Simulink for the selected Battery-SC
HESS were carried out, and their effectiveness in mitigating battery stress was
investigated and compared. The simulation analysis and results have been verified by
experiments with the developed prototype of hybrid energy storage system under
consideration. A battery healthy cost function that quantitatively evaluates the impact of
the damaging factors on the Lead-acid battery was proposed in this work. This allows
the effectiveness of different HESSs in mitigating battery operation stress to be
evaluated and compared. Furthermore, the proposed battery health cost model can be
used to analyze the economic improvement of the stand-alone PV power system by
estimating the extension in battery service life as a result of stress mitigation. Their
performances and effectiveness in stress mitigation were examined with a lab-scaled
prototype of HESS under consideration. The experimental outcomes verify the
theoretical analysis and simulation results done in this work. Simulation results, battery
health cost and financial analyses, and empirical outcomes suggest that the combination
of active secondary energy storage with the passive primary battery could be the
optimal setting for standalone PV power system applications.
Chapter 7 Conclusion and Future Work
- 151 -
To leverage on existing infrastructure in installed stand-alone PV-battery power system,
a smart HESS plug-in module (SHESS) was proposed in Chapter 6 to complement the
ESS operation. The design and development of the retrofittable SHESS module were
systematically presented, including the control system and power allocation strategy
used. The effectiveness of the proposed SHESS plug-in module in mitigating battery
operation stress was simulated in Matlab Simulink with actual solar irradiance data and
estimated load profile for a rural community in Sarawak Malaysia. Based on the
simulation results, the battery healthy cost analysis suggests that the battery lifetime can
be enhanced through mitigating damaging loading current to the primary battery bank,
hence reduction in overall system operating cost can be achieved. The analysis shows
that after installing the SHESS plug-in module, the annual operating cost can be reduced
up to 53.7%. The prototype of the proposed SHESS was constructed, and the
experimental results demonstrate the feasibility of being integrated into existing
installed PV-battery power system and the effectiveness of the proposed SHESS are in
good agreement with the simulation outcomes.
7.2 Future work
In this study, Battery-SC HESSs were implemented in stand-alone PV power system to
mitigate the primary Lead-acid battery operating stress factors. Throughout the research
and development work, progress was made in discovering promising directions which
could not be achieved because of time and/or scope considerations. Based on the
presented research work in this thesis, the following suggestions are provided for further
explorations:
(1) EMS optimization with SoC and temperature management
In this work, the design of EMS mainly focuses on power allocation strategy and
power-sharing capability without accurately evaluating and managing the real-time SoC
of energy storage devices and considering the effect of battery temperature into the
optimization processes. In EMS, the estimation and management of battery SoC, as well
as temperature monitoring, are also two of the essential aspects to be addressed. These
two parameters should be accurately monitored and controlled for performance
Chapter 7 Conclusion and Future Work
- 152 -
optimization. SoC estimation can be achieved by complementing sophisticated
approximation algorithms, empirical and statistical data. Therefore, one of the main
focuses of the extension of this work will be to devise an accurate and reliable battery
SoC estimation method that will serve as a useful parameter for the battery performance
optimization process. Moreover, at the same time, take into consideration of battery
temperature into the EMS and performance optimization process.
(2) HESS prototype in actual sized PV-battery power system
The proof-of-concept prototypes of the proposed SHESS plug-in module were
developed and tested in the lab-scaled facility. Research and development work can be
extended to design and develop an actual working prototype of the proposed SHESS
and to be tested in the real PV-battery power system to verify the feasibility of the
proposed system further. In addition, proof-of-concept to commercialization will be one
of the main aims of this research work.
(3) Demand-side management and load prediction
In this study, energy storage in HESS is designed to absorb/supply the power mismatch
between renewable energy sources and load in real-time, without considering demand-
side management such as load forecasting and demand response. If the load forecast can
be included in the energy management scheme, the power allocation strategy among
energy storage elements can be pre-determined (in a more optimal way) rather than
passively responding to it. For HESS design, future works include integration of
demand-side management into the optimization process, and daily/hourly load
prediction algorithm shall be considered in order to improve the efficiency and
sustainability of the overall system further.
(4) Battery healthy cost function extension
The battery health cost function proposed in this study considered five major life-
limiting factors that would have a negative impact on battery life. Exploration of other
internal or external factors that contribute to the aging process of battery should be one
of the major direction of the extension of this work. This would significantly improve
Chapter 7 Conclusion and Future Work
- 153 -
the model accuracy of the complex lifetime characteristic of battery and thus, providing
a more realistic battery state-of-health assessment.
(5) Battery lifetime characteristic study and evaluation
The Battery-SC HESSs in this study are designed to mitigate the operating pressure of
Lead-acid battery in stand-alone PV power systems and thus extend battery lifetime.
However, the exact extended lifetime of the Lead-acid battery under HESS is not given
in this study. Future work could involve organizing a series of experiments to assess the
Lead-acid battery operation lifetime in different HESS topologies, which provides
reliable evidence on battery lifetime extension and economic improvement with HESS
and thus commercialization can be realized.
- 154 -
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Appendix
A.1. Case study
Stand-alone PV-battery Power System for Batang Ai National Park Headquarter
(BANP)
A.1.1 Existing power generation and distribution system in BANP
Two major buildings are supplied with electricity namely the main office and Barrack A
(staff quarter) as shown in Fig. A.1.
Barrack A(User 1 - 6)
Main
Office
Main Office Distribution box
Barrack A Distribution Box
N
Genset Room
Main Distribution box
Fig. A.1 Layout of BANP and current electricity supply system
Barrack A is a longhouse-liked terrace that houses 6 families in total. Currently, a
5.6KVA petrol generator is used to supply electricity in BANP. In normal day, the
generator will be operated on average 3 hours in between 9am-1pm to carry out routine
Appendix
- 173 -
work on PC, and 6pm-11pm for basic electricity needs for the residents in Barrack A.
Their primary source of power is diesel generators and can only be started at specific
times. Based on the power consumption data collected during site visit on 28 March
2016, the power consumption pattern of the 2 main buildings is shown in Fig. A.2. The
barrack A consumes on average 1.4KW at night while the office consumes an additional
300W-500W on top of the Barrack A. A summary of electrical appliances that are
currently in use are tabulated in Table A.1.
Table A.1 Electrical appliances (currently in-use) of main office and barrack A
User Lighting
(20W) Fan Entertainment
Portable
Device
Refrigerator
/ Freezer
PC
workstation
Office 5 1 - - - 3
1 5 1 1 Radio 5 2-door -
2 5 1 1 TV + Astro 5 Freezer -
3 4 - - - - -
4 5 1 1 TV + Astro 3 - -
5 4 - - 1 - -
6 4 1 - 1 1-door -
As can be seen from the graph in Fig. A.2, the average load consumption is
approximately half the rated power of the petrol generator.
Time (hour)
Pow
er (k
W)
0 4 8 12 16 20 24
1
2
5.6KVA Petrol GensetEstimated fuel consumption (½ load) = 2.1L/hr Estimated fuel consumption (rated load)= 2.9L/hrEstimated fuel price = RM 2.80 / L (including transportation)
~4 Rated Load (Genset)
GENSET OFF
GENSET ON
Estimated load Power
Estimated daily fuel consumption ~= 16L (RM45)
Lite
r (L)
5
10
15
20
Estimated Fuel Consumption
BarrackA Barrack
A
Office
Fig. A.2 Existing power consumption pattern of BANP
Appendix
- 174 -
Based on the estimated fuel consumption of 2.1L/hour at 50% of rated load, the site is
consuming on average 16L of petrol which cost about RM45 for one ordinary day (not
including the transportation cost of petrol).
A.1.2 Proposed solar-battery-generator hybrid power system
(a) Stand-alone PV power system deign
Based on the power usage survey conducted, the site is estimated to consume on average
10kWh of energy per day. This power consumption estimation includes basic electricity
needs for barrack A and lighting consumption of the main office only. To provide
sufficient energy to this demand, a 2KWp solar array is proposed to generate on average
90% of the demand (based on average 4.5 sun hours), and the existing generator will be
used to top up the remaining 10% of the energy demand. Deep cycle Lead-acid battery
bank rated at 48V 600Ah will be used as the intermediate buffer for imbalance
generation and load. Fig. A.3 shows the design of the proposed stand-alone PV based
microgrid system to be implemented in BANP.
Barrack A
Main
Office
Proposed 2kWp Solar array Installation Site (S-1)
MPPT Charge Controller (48V 45A ~2.2KW)Battery (Lead Acid 48V 600Ah)Inverter/charger ~3KVA (D-1)
Main Office Distribution box (D-2)
Barrack A Distribution Box (D-3)
N
B
Genset Room
G
5.6KVA Petrol Generator (S-2)
(C-1)
(C-2)
(C-3)
Fig. A.3 Physical settings of the proposed system
Table A.2 summarized the required equipment and cables. Fig. A.4 presents the
connection diagram of the stand-alone PV power system.
Appendix
- 175 -
Table A.2 Solar installation checklist
S-2
D-1S-1
D-3
Solar Array8 X 250Wp (4S 2P)Peak Power: 2kWVmp: 121.36VImp: 16.48A
+-
Charge ControllerSystem Voltage: 48VMax Current: 45A
PV+
PV- BAT-BAT+
Lead Acid Battery 48V 600Ah24 X (12V 100Ah)Configuration: 4S 6P
Inverter / ChargerRated Power: 3KVASurge Power: 6KVACharge Current: ??
DC+
DC-
AC Out+
AC Out
-
D-2
+-
Combiner Block
2P MC
B
(20A)
Ground Busbar
1P MC
B
(50A)
1P MC
B
(50A)
Neutral LinkNeutral Line
13A
5A 5A
RC
D
20A
Barrack A
LightingB
arrack A Socket
Main O
ffice Lighting
AC In+
AC In-
C-2
C-1
Petrol GeneratorRated Power: 5.6kVA
+ -
C-3
13AM
ain Office Equipm
ent Fig. A.4 Connection diagram of the proposed system
Sub-system Device / Equipment Parameters / Specifications / Configuration
S-1
Promelight Polycrystalline solar panel (PT-
P660250BB)
8 x 250Wp
Array configuration: 4S 2P
Vmp = 121.36V
Imp = 16.48A
S-2 Petrol Genset (existing) Rated Power: 5.6KVA
C-1 DC cable Cable length: 25m
Cable size: 5AWG (16mm2)
C-2 AC Cable Cable length: 80m
C-3 AC Cable Cable length: 30m
D-1
Morning Star TriStar MPPT Charge
Controller
Max Current: 45A
Max Solar Voltage: 150V
Max solar power: 2.2kW (48V System)
Lead-acid Battery 24 x (12V 100Ah) Lead-acid Battery (4S 2P)
Total Capacity: 28.8kWh
OPTI Inverter / Charger
MCB 2-pole DC MCB:
1-pole DC MCB:
D-2
Main circuit breaker
RCD
Line circuit breaker
D-3 Line circuit breaker
Appendix
- 176 -
(b) Photos of on-site installation
Fig. A.5 PV panels installation and research team
Fig. A.6 Control system installation (MPPT + OPTI-Solar Controller)
Appendix
- 177 -
Fig. A.7 Main switches installation (Load+PV+Battery+Controller)
Fig. A.8 2400Ah PK200-12 Lead-acid battery bank Installation
Appendix
- 178 -
Fig. A.9 Actual load profile collection
A.2. Buck-boost DC/DC converter control and codes
A.2.1 The hardware structure
Fig. A.10 illustrates the system architecture diagram of the DC-DC converter system
that is based on a digital control strategy. The system includes the main power circuit,
the interface circuit, and the control circuit which incorporates the microprocessor and
external devices.
Peripheral(Power Supply,Computer, etc.)
DSPTMS320F28335
DAC or IO Peripheral Circuit
ADCSampling
Circuit
PWMPeripheral Circuit
Driver Circuit
Main Power Circuit
Interface Circuit
Fig. A.10 The system architecture diagram of DC/DC converter
Appendix
- 179 -
The main power circuit is composed of DC/DC converters and energy storage devices.
The interface circuit consists of three main parts. The first part is the Digital to Analog
Converter (DAC) and a peripheral circuit which contain IO ports. The second part
contains the external circuits for receiving the PWM signal and the corresponding drive
circuits. The third part is the feedback loop which consists of an Analog to Digital
Converter (ADC) and its sampling circuits. The interface circuit acts as a bridge to
connect the main power circuit to the microprocessor. The digital signal from the
microprocessor will be converted into an analog signal, and then it is used to control the
main power circuit. In turn, the analog signal from the main power circuit will be
sampled and converted into a digital signal, which is then fed back to the
microprocessor. The microprocessor will adjust the output control signal automatically
and finally improve the stability of the entire system. The prototype of the buck-boost
DC/DC converter is shown in Fig. A.11.
Fig. A.11 The bidirectional buck-boost DC/DC converter
A.2.2 Control code in Arduino microprocessor
(a) Code for Semi-Active SC HESS Control
#include <PID_v1.h>
#include <PID_buck.h>
#include <PID_boost.h>
const int pwm_in = 5;
const int pwm_sd = 6;
const int current_pin = 0;
Appendix
- 180 -
const int current1_pin = 1;
double amps_raw = 0; // value from acs712
double amps_actual = 0; // actual current
double amps_desired = 0; // desired current
double amps_desired_last = 0;
double amps_diff = 0;
double pwm_dc = 0; // dc = duty cycle
double pwm_dc_last = 0;
int i = 0;
int a = 0;
int b = 0;
const int sampleTime = 1;//1714*2
const int numReadings = 20 ;
double readings[numReadings];
int readIndex = 0;
double total = 0;
double average = 0;
double aggKp = 0.5, aggKi = 50, aggKd = 0;
double consKp = 0.5, consKi = 50, consKd = 0;
PIDBUCK buckPID(&s_actual, &pwm_dc, &s_desired, consKp, consKi, consKd,
DIRECT);
PIDBOOST boostPID(&s_actual, &pwm_dc, &s_desired, consKp, consKi, consKd,
DIRECT);
void setup(){
// Change prescale to 1 for max PWM frequency - 62.5kHz
TCCR0B = (TCCR0B & 0b11111000) | 0x01;
// Declaring pin to be input or output
pinMode(current_pin, INPUT);
pinMode(current1_pin, INPUT);
amps_actual = 0;
Appendix
- 181 -
amps_desired = 0;
pwm_dc = 0;
i = 0;
Serial.begin(9600);
buckPID.SetMode(AUTOMATIC);
boostPID.SetMode(AUTOMATIC);
buckPID.SetOutputLimits(125,255);
boostPID.SetOutputLimits(105,255);
for (int thisReading = 0; thisReading < numReadings; thisReading++){
readings[thisReading] = 0;
}
}
void loop(){
amps_actual = ((510 - analogRead(current_pin)) * (5/0.185) / 1024)*(-1);
amps_diff = ((509 - analogRead(current1_pin)) * (5/0.1) / 1024);
if (i < sampleTime){
i++;
} else if (i == sampleTime){
total = total - readings[readIndex];
readings[readIndex] = amps_diff;
total = total + readings[readIndex];
readIndex = readIndex + 1;
if (readIndex >= numReadings){
readIndex = 0;
}
i = 0;
}
amps_desired = amps_diff - (total / numReadings);
amps_desired = (amps_desired + amps_desired_last) / 2;
Appendix
- 182 -
amps_desired_last = amps_desired;
double gap = abs(amps_desired - amps_actual);
if (gap < 0.5){
buckPID.SetTunings(consKp, consKi, consKd);
boostPID.SetTunings(consKp, consKi, consKd);
} else{
buckPID.SetTunings(aggKp, aggKi, aggKd);
boostPID.SetTunings(aggKp, aggKi, aggKd);
}
if (amps_desired > 0){
if (amps_desired <= 0.04 && a == 0){
a = 1;
} else if (amps_desired <= 0.1 && a == 1){
if (amps_desired > 0.07){
a = 0;
}
} else {
TCCR0A = TCCR0A & 0b11101111;
buckPID.Compute();
Serial.print("buck ");
}
} else if (amps_desired < 0){
if (amps_desired >= -0.04 && b == 0){
b = 1;
} else if (amps_desired >= -0.1 && b == 1){
if (amps_desired < -0.07){
b = 0;
}
} else {
TCCR0A = TCCR0A | 0b00110000;
boostPID.Compute();
Serial.print("boost ");
}
}
Appendix
- 183 -
if (pwm_dc < 0){
pwm_dc = 0;
}
if (pwm_dc > 253){
pwm_dc = 254;
}
analogWrite(pwm_in, pwm_dc);
analogWrite(pwm_sd, pwm_dc);
Serial.print(amps_desired,5);
Serial.print(",");
Serial.print(amps_actual,5);
Serial.print(",");
Serial.print(amps_diff,5);
Serial.print(",");
Serial.println(pwm_dc);
}
(b) Code for SC/Lithium-ion HESS Control
#include <PID_buck.h>
#include <PID_boost.h>
// Inverted signal on IN of gate driver
// Non-inverter signal on SD of gate driver
// COMnA1 | COMnA0 | COMnB1 | COMnB0
const int pwm_6 = 6; // OC0A
const int pwm_5 = 5; // OC0B
const int pwm_9 = 9; // OC1A
const int pwm_10 = 10; // OC1B
const int pwm_11 = 11; // OC2A
const int pwm_3 = 3; // OC2B
const int current_converter_sc_pin = 0;
const int current_converter_batt_2_pin = 2;
const int current_hess_pin = 1;
Appendix
- 184 -
double amps_hess = 0; // pv - load current
double amps_batt_1 = 0;
float wf = 0.9; // weight factor
// For supercap converter
double amps_converter_sc = 0; // actual current amps_actual
double amps_sc = 0; // desired current amps_desired
double amps_sc_last = 0;
double pwm_sc = 0; // dc = duty cycle
int a = 0;
int b = 0;
// For battery 2 converter
double amps_converter_batt_2 = 0; // actual current in converter battery 2
double amps_batt_2 = 0; // desired battery 2 current
double amps_batt_2_last = 0;
double pwm_batt_2 = 0; // pwm signal for converter battery 2
int c = 0;
int d = 0;
// For battery 1 averaging (primary)
const int sampleTime_batt_1 = 1/0.055*180; // 1/0.055 = 1s
const int numReadings_batt_1 = 20 ;
double readings_batt_1[numReadings_batt_1];
int readIndex_batt_1 = 0;
double total_batt_1 = 0;
int i = 0;
// For battery 2 averaging (secondary)
const int sampleTime_batt_2 = 1/0.055*60;// 1/0.055 = 1s
const int numReadings_batt_2 = 20 ;
double readings_batt_2[numReadings_batt_2];
int readIndex_batt_2 = 0;
double total_batt_2 = 0;
int j = 0;
Appendix
- 185 -
unsigned int time = 0;
double aggKp = 0.5, aggKi = 50, aggKd = 0;
double consKp = 0.5, consKi = 50, consKd = 0;
PIDBUCK buck_sc_PID(&s_converter_sc, &pwm_sc, &s_sc, consKp, consKi, consKd,
DIRECT);
PIDBOOST boost_sc_PID(&s_converter_sc, &pwm_sc, &s_sc, consKp, consKi,
consKd, DIRECT);
PIDBUCK buck_batt_2_PID(&s_converter_batt_2, &pwm_batt_2, &s_batt_2, consKp,
consKi, consKd, DIRECT);
PIDBOOST boost_batt_2_PID(&s_converter_batt_2, &pwm_batt_2, &s_batt_2,
consKp, consKi, consKd, DIRECT);
void setup() {
// Change prescale to 1 for max PWM frequency - 62.5kHz
// TCCR0B = (TCCR0B & 0b11111000) | 0x01;
TCCR1A = (TCCR1A & 0b11111100) | 0b00000001; // _BV(WGM10)
TCCR1B = (TCCR1B & 0b11100000) | 0b00001001; // _BV(WGM12) | _BV(CS10)
TCCR2A = (TCCR2A & 0b11111100) | 0b00000011; // _BV(WGM21) | _BV(WGM20)
TCCR2B = (TCCR2B & 0b11110000) | 0b00000001; // _BV(CS20)
// Declaring pin to be input or output
pinMode(current_converter_sc_pin, INPUT);
pinMode(current_converter_batt_2_pin, INPUT);
pinMode(current_hess_pin, INPUT);
amps_converter_sc = 0;
amps_sc = 0;
pwm_sc = 0;
i = 0;
Serial.begin(9600);
buck_sc_PID.SetMode(AUTOMATIC);
boost_sc_PID.SetMode(AUTOMATIC);
buck_batt_2_PID.SetMode(AUTOMATIC);
Appendix
- 186 -
boost_batt_2_PID.SetMode(AUTOMATIC);
buck_sc_PID.SetOutputLimits(0, 255);
boost_sc_PID.SetOutputLimits(0, 255);
buck_batt_2_PID.SetOutputLimits(0, 255);
boost_batt_2_PID.SetOutputLimits(0, 255);
buck_sc_PID.SetTunings(consKp, consKi, consKd);
boost_sc_PID.SetTunings(consKp, consKi, consKd);
buck_batt_2_PID.SetTunings(consKp, consKi, consKd);
boost_batt_2_PID.SetTunings(consKp, consKi, consKd);
for (int thisReading_batt_1 = 0; thisReading_batt_1 < numReadings_batt_1;
thisReading_batt_1++) {
readings_batt_1[thisReading_batt_1] = 0;
}
for (int thisReading_batt_2 = 0; thisReading_batt_2 < numReadings_batt_2;
thisReading_batt_2++) {
readings_batt_2[thisReading_batt_2] = 0;
}
}
void loop() {
time = micros();
amps_converter_sc = ((512 - analogRead(current_converter_sc_pin)) * (5 / 0.185) / 1024) * (-
1);
amps_converter_batt_2 = ((512 - analogRead(current_converter_batt_2_pin)) * (5 / 0.185) /
1024) * (-1);
amps_hess = ((509 - analogRead(current_hess_pin)) * (5 / 0.1) / 1024);
if (i < sampleTime_batt_1) {
i++;
} else if (i == sampleTime_batt_1) {
total_batt_1 = total_batt_1 - readings_batt_1[readIndex_batt_1];
readings_batt_1[readIndex_batt_1] = amps_hess;
total_batt_1 = total_batt_1 + readings_batt_1[readIndex_batt_1];
readIndex_batt_1 = readIndex_batt_1 + 1;
Appendix
- 187 -
if (readIndex_batt_1 >= numReadings_batt_1) {
readIndex_batt_1 = 0;
}
i = 0;
}
amps_batt_1 = (total_batt_1/numReadings_batt_1) * wf;
if (j < sampleTime_batt_2) {
j++;
} else if (j == sampleTime_batt_2) {
total_batt_2 = total_batt_2 - readings_batt_2[readIndex_batt_2];
readings_batt_2[readIndex_batt_2] = amps_hess - amps_batt_1;
total_batt_2 = total_batt_2 + readings_batt_2[readIndex_batt_2];
readIndex_batt_2 = readIndex_batt_2 + 1;
if (readIndex_batt_2 >= numReadings_batt_2) {
readIndex_batt_2 = 0;
}
j = 0;
}
amps_batt_2 = (total_batt_2/numReadings_batt_2);
amps_sc = amps_hess - amps_batt_1 - amps_batt_2;
amps_sc = (amps_sc + amps_sc_last) / 2;
amps_sc_last = amps_sc;
// PI
if (amps_sc > 0) {
if (amps_sc <= 0.04 && a == 0) {
a = 1;
} else if (amps_sc <= 0.1 && a == 1) {
if (amps_sc > 0.07) {
a = 0;
}
Appendix
- 188 -
} else {
buck_sc_PID.Compute();
output_pwm_sc();
TCCR1A = TCCR1A & 0b10111111;
}
} else if (amps_sc < 0) {
if (amps_sc >= -0.04 && b == 0) {
b = 1;
} else if (amps_sc >= -0.1 && b == 1) {
if (amps_sc < -0.07) {
b = 0;
}
} else {
boost_sc_PID.Compute();
output_pwm_sc();
TCCR1A = TCCR1A | 0b11000000;
}
}
if (amps_batt_2 > 0) {
if (amps_batt_2 <= 0.04 && c == 0) {
c = 1;
} else if (amps_batt_2 <= 0.1 && c == 1) {
if (amps_batt_2 > 0.07) {
c = 0;
}
} else {
buck_batt_2_PID.Compute();
output_pwm_batt_2();
TCCR2A = TCCR2A & 0b10111111;
}
} else if (amps_batt_2 < 0) {
if (amps_batt_2 >= -0.04 && d == 0) {
d = 1;
} else if (amps_batt_2 >= -0.1 && d == 1) {
if (amps_batt_2 < -0.07) {
d = 0;
Appendix
- 189 -
}
} else {
boost_batt_2_PID.Compute();
output_pwm_batt_2();
TCCR2A = TCCR2A | 0b11000000;
}
}
Serial.print(amps_sc, 5);
Serial.print(" ");
Serial.print(amps_converter_sc, 5);
Serial.print(" ");
Serial.print(amps_batt_2, 5);
Serial.print(" ");
Serial.print(amps_converter_batt_2, 5);
Serial.print(" ");
Serial.println(amps_hess, 5);
Serial.print(" ");
Serial.print(pwm_sc);
Serial.print(" ");
Serial.println(pwm_batt_2);
}
void output_pwm_sc(){
if (pwm_sc < 0) {
pwm_sc = 0;
}
if (pwm_sc > 253) {
pwm_sc = 254;
}
analogWrite(pwm_9, pwm_sc); // inverted
analogWrite(pwm_10, pwm_sc);
}
void output_pwm_batt_2(){
Appendix
- 190 -
if (pwm_batt_2 < 0) {
pwm_batt_2 = 0;
}
if (pwm_batt_2 > 253) {
pwm_batt_2 = 254;
}
analogWrite(pwm_3, pwm_batt_2);
analogWrite(pwm_11, pwm_batt_2); // inverted
}