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Dynamic Modeling, Simulation and Control of a Small Wind-Fuel Cell Hybrid Energy System for

Stand-Alone Applications

Mohammad Jahangir Khanmjakhan@engr.mun.ca

Faculty of Engineering & Applied ScienceElectrical Engineering

Graduate Student Seminar : Master of Engineering

June 29, 2004

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Outline Introduction

• Renewable Energy, Hybrid & Stand-alone Power Sources

• Emerging Technologies, Scope of Research Pre-feasibility Study

• Load, Resource, Technology Options• Sensitivity & Optimization Results

Model Formulation• Wind Energy Conversion System, Fuel Cell System,

Electrolyzer, Power Converter• System Integration

Simulation Results

• Random Wind Variation• Step Response

Conclusion

Introduction 3

Canada and the Global Energy Scenario • At present, proportion of renewable energy in the global

energy mix is about 14 % only.• Various environmental regulations and protocols aim at

increasing this ratio towards 50% by 2050.

Source: German Advisory Council on Global Change

Introduction 4

• In Canada, utilization of renewable resources is less than 1 % (excluding hydroelectricity)

• Vast wind energy potential is mostly unexplored.

Source: The Conference Board of Canada Source: Natural Resources Canada

Introduction 5

Emerging Technologies in Energy Engineering

• Wind and Solar energy technologies are the forerunners• Hydrogen based energy conversion bears good potential

Source: Worldwatch Institute Source: Plug Power Inc., NY

Introduction 6

Hybrid Energy Systems in Stand-alone Applications

• Energy from a renewable source depends on environmental conditions

• In a Hybrid Energy System, a renewable source is combined with energy storage and secondary power source(s).

• Mostly used in off-grid/remote applications• Could be tied with a distributed power generation network.

Introduction 7

Wind-Fuel Cell Hybrid Energy System• A wind turbine works as a primary power source• Availability of wind energy is of intermittent nature• Excess energy could be used for hydrogen production by an

electrolyzer• During low winds, a fuel-cell delivers the electrical energy using

the stored hydrogen• Radiated heat could be used for space heating• Power converters and controllers are required to integrate the

system

Introduction 8

Scope of Research

Q1. Is a wind-fuel cell hybrid energy system feasible for a given set of conditions?

• Pre-feasibility Study• Site: St. John’s, Newfoundland.

Q2. What are the alternatives for building and testing a HES, provided component cost is very high and technology risk is substantial?

• Computer aided modeling• System integration and performance analysis through

simulation

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Pre-feasibility Study

Investigation of technology options, configurations and economics using:

• Electrical load profile • Availability of renewable resources• Cost of components (capital, O&M)• Technology alternatives• Economics & constraints• HOMER (optimization software)

Pre-feasibility Study 10

HOMER Implementation

• St. John’s, Newfoundland• Renewable (wind/solar) & non-

renewable (Diesel generator) sources• Conventional (Battery) & non-

conventional (Hydrogen) energy storage

• Sensitivity analysis with wind data, solar irradiation, fuel cell cost & diesel price.

Pre-feasibility Study 11

Electrical Load• A typical grid connected home may consume around

50 kWh/d (peak 15 kW)• A HES is not suitable for such a large load• Off-grid/remote homes should be designed with

energy conservation measures• A house with 25 kWh/d (4.73 kW peak) is considered• Actual data is scaled down

Source: Newfoundland Hydro

Pre-feasibility Study 12

Renewable Resources

• Hourly wind data for one year at St. John’s Airport.

• Average wind speed in St. John’s is around 6.64 m/s.

• Hourly solar data for one year at St. John’s Airport.

• Average solar irradiation in St. John’s is around 3.15 kWh/d/m2.

Pre-feasibility Study 13

Components

• Wind turbine• Solar array• Fuel cell• Diesel generator• Electrolyzer • Battery • Power converter

Pre-feasibility Study 14

Sensitivity Results

• At present, a wind/diesel/battery system is the most economic solution

• Solar energy in Newfoundland is not promising

Pre-feasibility Study 15

• A wind/fuel cell/diesel/battery system would be feasible if the fuel cell cost drops around 65%.

• A wind/fuel cell HES would be cost-effective if the fuel cell cost decreases to 15% of its present value

Pre-feasibility Study 16

Optimization Results

Considering :

• wind speed = 6.64 m/s• solar irradiation = 3.15 kWh/m2/d • Diesel price = 0.35 $/L

The optimum solutions are:

Pre-feasibility Study 17

Wind-Fuel Cell System Optimization

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Model Formulation

Models Developed for:

• Wind Turbine (7.5 kW): Bergey Excel-R • PEM Fuel Cell (3.5 kW): Ballard MK5-E type • Electrolyzer (7.5 kW): PHOEUBS type • Power Converters (3.5 kW)

Approach:

• Empirical & physical relationships used• Components are integrated into a complete

system through control and power electronic interfaces

• Simulation done in MATLAB-Simulink®

Model Formulation 19

Wind Energy Conversion System (WECS)

Small wind turbine: BWC Excel-R type Wind field Rotor aerodynamics

• Spatial Filter• Induction Lag

PM DC generator Controller

• Reference speed generator• Fuzzy logic controller

Model Formulation 20

Small WECS

Power in the wind:

Captured power:

3windwtwind VA

2

1P ρ=

3effwtpa VA

2

1CP ρ=

Power 50 W ~ 10 KW

Diameter 1 ~ 7 m

Hub-height ~ 30 m

Control/Regulation Stall, Yaw, Pitch, Variable speed

Over-speed Protection Horizontal/Vertical furling

Generator DC, Permanent Magnet Alternator

Application Stand-alone, Grid connections

Model Formulation 21

Small WECS Model Formulation

Wind Field

4142.1s1598.1s1918.0

4142.1s43795.0=

V

V2

wind

filt

+++

)t(mVT

1

dt

dV

VVV

windturbv

turb

avgturbwind

+−=

+=

Spatial Filter & Induction Lag

1

1i

filt

eff

1s

1sa

V

V

τ

τ+

+=

ral IkT φ=

φωra kE =

aaa

aawt_t IRdt

dILEV −−=

ωωB

dt

dJTT r

la ++=

PM DC Generator

Model Formulation 22

Controller DesignControl Problem

I. Below rated wind speed: Extract maximum available power

II. Near-rated wind speed:Maintain constant rated power

III. Over-rated wind speed : Decrease rotor speed (shut-down)

Control method

A PD-type fuzzy logic controller (FLC) is employ

Reference rotor speed is estimated from rotor torque

Difference in actual & ref. Speed is used to control the dump load

I II III

Model Formulation 23

Determination of Ref. Rotor Speed Rotor torque is assumed available

Below rated reference rotor speed:

Near-rated conditions:

Over-rated reference rotor speed:

'aw

T

'a

ref Tkk

T ==ω

roref ωω =

'T

P

a

maxref =ω

Model Formulation 24

Design of Fuzzy Logic Controller

A PD type FLC is used for the whole range of wind variation

Variable Identification: Error & Rate of change of errorFuzzification: Five Gaussian membership functions for all variablesRules of inference: Fuzzy Associative MemoryDefuzzification: Centroid method (Mamdani)

Model Formulation 25

Summary

Dynamic model of a Small wind turbine (BWC Excel-R type) Wind field, Rotor aerodynamics, PM DC generator Controller (Reference speed generator, Fuzzy logic controller) Mechanical sensorless control (rotor torque assumed

estimable)

Model Formulation 26

Fuel Cell System

PEM fuel cell: Ballard MK5-E type Empirical & physical expressions Electrochemistry Dynamic energy balance Reactant flow Air flow controller

Model Formulation 27

PEM Fuel Cells

Polymer membrane is sandwiched between two electrodes, containing a gas diffusion layer (GDL) and a thin catalyst layer.

The membrane-electrode assembly (MEA) is pressed by two conductive plates containing channels to allow reactant flow.

H2

H2

H2

O2

O2

O2

Gas diffusion layer

Flow channels

Catalyst later

Conductive plates

Electrolyte

Electric load

Anode Cathode

FuelI In

H2

H2O

1/2O2

H2O

Electrolyte

Oxidant in

Depleted Fuel Depleted oxidant

Positive Ion

Negative Ion

2e-Load

Model Formulation 28

Fuel Cell Model FormulationElectrochemical Model Cell voltage & Stack voltage:

Open circuit voltage:

Activation overvoltage:

Ohmic overvoltage

ohmicactNernstcell EV ηη ++=

ENernst

Ract

Rint

Cdl

+

Vcell

-

Ifc

dlact

act

dl

fcact

CR

V-

C

I=

dt

dV

intfcohmic RI−=η

actactV η−=

cellfcstack VNV =

( )[ ]5.0'O

'H

fcfc

3-Nernst 22

pplnF2

RT)+15.298-(T10×5.8229.1=E −

Model Formulation 29

Reactant Flow Model Performance depends on oxygen,

hydrogen & vapor pressure Anode & Cathode flow models

determine reactant pressures Ideal gas law equations and principles

of mole conservation are employed

nF

I±m-m=

dt

dP

RT

Vout

•

in

•g

)P-k(P=m ambgout

•

Model Formulation 30

Thermal Model Fuel cell voltage depends on stack temperature Stack temperature depends on load current, cooling, etc. Total power (from hydrogen) =

Electrical output + Cooling + Surface Loss + Stack Heating A first order model based on stack heat capacity is used

Total power

Surface heat loss

Cooling system heat removal

Electric powerStack heating

fcstack_

•'

fcfc_t Q=

dt

dTC

fc_loss

•

fc_cool

•

fcfc_tot

'fc

fc_t QQPP=dt

dTC −−−

Model Formulation 31

Summary

Dynamic model of a PEM fuel cell (Ballard MK5-E type) Electrochemical, thermal and reactant flow dynamics

included Model shows good match with test results

Model Formulation 32

Electrolyzer

Alkaline Electrolyzer: PHOEBUS type Empirical & physical expressions Electrochemistry Dynamic energy balance

Model Formulation 33

Alkaline Electrolyzer

Aqueous KOH is used as electrolyte Construction similar to fuel cell

Model Formulation 34

Electrolyzer Model FormulationElectrochemical Model Cell voltage:

Faraday efficiency:

Hydrogen production:

Thermal Model

+

+++

++= 1I

A

T/tT/ttlogsI

A

TrrUU elz

elz

2elz3elz21

elzelz

elz21revcell

( )( ) 22

elzelz1

2elzelz

F fA/If

A/I

+=η

elzelz

FH IzF

Nn 2 η=•

elzstack_

•elz

elz_t Q=dt

dTC

elz_loss

•

elz_cool

•

elzstack_

•

elz_gen

•

QQQQ ++=

Model Formulation 35

Power Electronic Converters

• Variable DC output of the Wind turbine/Fuel cell is interfaced with a 200 V DC bus

• Load voltage: 120 V, 60Hz• Steady state modeling of DC-DC converters• Simplified inverter model coupled with LC filter• PID controllers used

Model Formulation 36

Power Converter Models

WECS Buck-Boost Converter

Inverter, Filter & R-L Load

wt

wt

wt_t

bus

D1

D

V

V

−=

fcstack

bus

D1

1

V

V

−=

Fuel Cell Boost Converter

Model Formulation 37

System Integration

Positive

Wind Power

Start

Wind Power-Load Power

Load Power

Excess Power

Electrolzyer

DeficitPower

Fuel Cell

End

YN

Wind-fuel cell system interconnection

Power flow control

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MATLAB-Simulink® Simulation

Simulation 39

Simulation time = 15 seconds Constant temperature in fuel cell & electrolyzer assumed Step changes in

• Wind speed• Load resistance• Hydrogen pressure

Simulation

Results 40

Results System response with random wind

Results 41

WECS performance (step response)

Results 42

Power balance (step response)

Results 43

Fuel cell performance (step response)

Results 44

Electrolyzer performance (step response)

Results 45

Power converter performance (step response)

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Summary

Highest settling time for the wind turbine Controlled operation of the wind turbine, fuel cell,

electrolyzer and power converter found to be satisfactory Coordination of power flow within the system achieved

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Contributions

For a stand-alone residential load in St. John’s, consuming 25 kWh/d (4.73 kW peak) a pre-feasibility study is carried out.

A mathematical model of wind-fuel cell energy system is developed, simulated and presented. The wind turbine model employs a concept of mechanical sensorless FLC.

The PEM fuel cell model unifies the electrochemical, thermal and reactant flow dynamics.

A number of papers generated through this work. Explored fields include:

• Wind resource assessment• Fuel cell modeling• Grid connected fuel cell systems• Small wind turbine modeling

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Conclusions

A wind-fuel cell hybrid energy system would be cost effective if the fuel cell cost reduces to 15% of its current price. Cost of energy for such a system would be around $0.427/kWh.

Performance of the system components and control methods were found to be satisfactory.

Improvement in relevant technologies and reduction in component cost are the key to success of alternative energy solutions.

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Further Work

Development of a faster model for investigating variations in system temperature and observing long term performance (daily-yearly).

Inclusion of various auxiliary devices into the fuel cell and electrolyzer system.

Use of stand-by batteries Research into newer technologies such as, low speed wind

turbines, reversible fuel cell etc. Comprehensive study of relevant power electronics and controls

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Acknowledgement

Faculty of Engineering & Applied Science, MUN. School of Graduate Studies, MUN. NSERC Environment Canada Dr. M. T. Iqbal. Drs. Quaicoe, Jeyasurya, Masek, and Rahman.

Thank You

Questions/Comments

For your attention & presence