Wind Following with Pumped Hydroelectric Energy Storage in

New Brunswick

by

Dorji Namgyel

B.E (EE), University of Rajasthan, India, 2004

A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of

Master of Science in Engineering

in the Graduate Academic Unit of Electrical and Computer Engineering

Supervisors: Dr. Liuchen Chang, BE (Northern Jiaotong), MScE (China

Academy of Railway Sciences), PhD (Queen's University)

Dr. Eugene F. Hill, BScE, MScE (UNB), PhD (NC State

University)

Mr. William K. Marshall, BScE, MScE (UNB), Past President,

New Brunswick System Operator (NBSO)

Examining Board: J. Meng, PhD, Electrical and Computer Engineering, Chair

C. P. Diduch, PhD, Electrical and Computer Engineering

A. Saleh, PhD, Electrical and Computer Engineering

R. Chaplin, PhD, Chemical Engineering

This thesis is accepted by the Dean of Graduate Studies

THE UNIVERSITY OF NEW BRUNSWICK

August, 2012

© Dorji Namgyel, 2012

ii

DEDICATION

I dedicate this thesis to my wonderful wife, Tshering Dema and our precious

daughter Pema Yewong who have always been my source of inspiration for two years I

lived away from them completing this thesis work. I must also thank my terrific in-laws

how have helped so much in baby-sitting and have given me their full support.

iii

ABSTRACT

With persistently increasing fuel prices and growing environmental concerns, the

energy from renewable resources, particularly wind energy is becoming immensely

popular throughout the world. However, the main drawback of wind power is its inherent

variability and uncertainty of source. This has ignited a renewed interest in Pumped

Hydroelectric Energy Storage (PHES) systems. PHES today is considered the most

effective method to overcome the wind variability problem. The province of New

Brunswick having set its renewable energy portfolio standard at 10% by 2016 has seen a

number of large scale wind power additions to the grid. In this thesis, the introduction of

PHES in the New Brunswick electric grid is investigated for its technical and economic

feasibility. PHES is being used as the means to balance wind variation and minimize the

overall generation cost of the New Brunswick power system.

iv

ACKNOWLEDGEMENTS

I would like to thank Dr. Eugene F. Hill, Retired Professor of Electrical

Engineering for his tremendous patience, his understanding and for all the time he spent

in successful completion of this work. I have gained a wealth of knowledge from him in

the process of completing this work. I will always remain indebted to him for all the help

he provided during my stay in Fredericton.

I would like to thank Dr. Liuchen Chang, Professor of Electrical Engineering for

his timely guidance and support which was a lot of contribution towards successful

completion of this thesis.

I would like to thank Mr. Fred Harriman and Mr. William K. Marshall for their

valuable feedback on the thesis. It was through their years of experience and immense

depth of knowledge in power utilities that helped giving shape and direction to this thesis.

I would like to thank Mr. Kenneth Scott Brown, Mr. George Potter and Mr. Craig

Church, New Brunswick System Operator for all the help they provided that helped in

timely completion of this thesis. It was through their recommendation that I got the

academic license for the software and through their help that I learned to use it

efficiently.

Finally, I would like to thank my parent company Druk Green Power Corporation

Ltd. for the trust they had in me by sending me for higher studies.

v

Table of Contents DEDICATION .................................................................................................................... ii

ABSTRACT iii ACKNOWLEDGEMENTS ............................................................................................... iv Table of Contents ................................................................................................................ v List of Tables ................................................................................................................... viii

List of Figures .................................................................................................................... ix Chapter 1: INTRODUCTION ......................................................................................... 1

1.1 General ................................................................................................................. 1

1.1.1 Overview of New Brunswick Power System ................................................ 2

1.2 Literature Review ................................................................................................. 4

1.2.1 Brief History of Pumped Hydroelectric Energy Storage .............................. 4

1.2.2 Benefits of Pumped Hydroelectric Energy Storage for Wind Integration .... 6

1.3 Motivation ............................................................................................................ 8

1.4 Objectives of the Thesis ..................................................................................... 10

Chapter 2: PUMPED HYDROELECTRIC ENERGY STORAGE .............................. 11 2.1 Overview ............................................................................................................ 11

2.2 Desirable Site Characteristics............................................................................. 12

2.3 Identification of PHES sites in New Brunswick ................................................ 14

2.3.1 Upper Reservoir .......................................................................................... 15

2.3.2 Lower Reservoir.......................................................................................... 16

2.3.3 Power House ............................................................................................... 16

2.3.4 Water Conduit ............................................................................................. 19

2.4 Capital Cost Estimate ......................................................................................... 19

2.5 Summary ............................................................................................................ 20

Chapter 3: POWER SYSTEM OPERATION OPTIMIZATION ................................. 21 3.1 Details of Power System Generating Units ........................................................ 21

3.1.1 Thermal Units ............................................................................................. 21

3.1.2 Hydro Units ................................................................................................. 22

3.1.3 Wind Farms ................................................................................................. 23

vi

3.2 Problem Explanation and Formulation .............................................................. 23

3.3 Solution Method ................................................................................................. 29

3.3.1 Branch and Bound Algorithm ..................................................................... 29

3.4 Software for Implementation ............................................................................. 31

3.5 Summary ............................................................................................................ 31

Chapter 4: INPUT DATA AND ASSUMPTIONS ....................................................... 33

4.1 Defining Thermal Units ..................................................................................... 33

4.2 Defining Hydro Units ......................................................................................... 34

4.3 Defining Wind Farms ......................................................................................... 35

4.4 Defining PHES unit ............................................................................................ 36

4.5 System Load Data .............................................................................................. 37

4.6 System Reserves ................................................................................................. 38

4.7 Transmission Line Losses .................................................................................. 39

4.8 Summary ............................................................................................................ 39

Chapter 5: RESULTS AND ANALYSIS ..................................................................... 41

5.1 Details of Test System Model ............................................................................ 41

5.2 Results for Test System Model .......................................................................... 44

5.2.1 Total Generation Cost of the System .......................................................... 44

5.2.2 Operation of PHES Unit ............................................................................. 46

5.3 Results of Practical System Model..................................................................... 47

5.3.1 Total Generation Cost of the System .......................................................... 48

5.3.2 Effect of PHES Unit in System Generation ................................................ 51

5.3.3 Operation of PHES Unit in the Power System ........................................... 53

5.3.4 Summary ..................................................................................................... 55

Chapter 6: CONCLUSIONS ......................................................................................... 56

6.1 Conclusions ........................................................................................................ 56

6.2 Recommendations for Future Work ................................................................... 58

vii

REFERENCES ................................................................................................................. 61 APPENDIX A ................................................................................................................... 64

Curriculum Vitae

viii

List of Tables

Table 1: Some Worldwide PHES facilities under construction ........................................ 20

Table 2: Monthly Average River Inflow of Hydro Units ................................................. 34

Table 3: Characteristics of the PHES Unit ....................................................................... 37

Table 4: Characteristics of Test System Units .................................................................. 41

Table 5: Savings in Total Generation Cost of the Practical System ................................. 49

Table 6: Total Generation and Pump Energy of PHES Unit ............................................ 51

Table 7: Category Wise Total Generation from Practical System Units .......................... 52

Table 8: Total Generation Cost of Test System with and without Constraint .................. 59

Table 9: Total Generation Cost of Practical System with Different Storage Targets ....... 60

Table 10: Characteristics of Thermal Units of Practical System Model .......................... 64

ix

List of Figures

Figure 1: Site Identified for Construction of a 20 MW PHES Unit ................................. 14

Figure 2: Proposed Site for PHES, Eel River and Annies Mountain................................ 15

Figure 3: Proposed 20 MW PHES in New Brunswick at Annies Mountain .................... 19

Figure 4: Classical Fuel Cost Curve of a Thermal Generator ........................................... 22

Figure 5: Hourly Wind Power Output Data ...................................................................... 36

Figure 6: Hourly Load Data of New Brunswick for 2010-2011 ....................................... 38

Figure 7: Monthly Average Natural Inflow for Hydro Unit of Test System .................... 42

Figure 8: Hourly Wind Power Data of Test System Wind Farm ...................................... 43

Figure 9: Hourly Load Data of Test System ..................................................................... 43

Figure 10: Total Monthly Generation Cost of the Test System ........................................ 44

Figure 11: Weekly Unit Wise Generation of the Test System.......................................... 45

Figure 12: Hourly Net Generation of Hydro Unit and PHES Unit of Test System .......... 46

Figure 13: Hourly Net Generation of PHES Unit and Energy Price of Test System ....... 47

Figure 14: Month Wise Generation Cost of the System without PHES Unit ................... 49

Figure 15: Month Wise Total Generation Cost of the Practical System........................... 50

Figure 16: Monthly Total Generation from the Wind Farm for Different Scenarios ....... 53

Figure 17: Operation Pattern of PHES Unit in Pumping Mode for Practical System ...... 54

Figure 18: Yearly Average System Load Pattern of the Practical System ....................... 54

1

Chapter 1

INTRODUCTION

1.1 General

Wind is a result of unequal heating of different parts of a location at different

rates. Wind energy is the conversion of kinetic energy of this air in motion (wind) into

electrical energy by means of wind turbines and is directly proportional to the cubic of its

speed. The main driving force behind increased wind power utilization is the growing

environmental concern due to emission from fossil fuels. As the industrial development

and consumption continue to grow rapidly around the globe wind, being a renewable and

sustainable resource and widely available, is a perfect energy source to supplement the

Green House Gas (GHG) emitting energy sources.

The main drawback of wind energy is the intermittent nature of its source. Wind

is extremely variable and there is no guarantee that it will blow when it is most needed.

For this reason, large scale integration of wind is a threat to the stability and reliability of

utility grids hosting wind energy conversion systems. Moreover, wind power does not

help in providing any of the ancillary services such as regulation reserves, voltage control

and frequency control and therefore requires a substantial capacity of conventional

energy generation that can provide regulation reserve to follow the wind power.

In a power system with abundant hydro generation, wind power balancing is

achieved quite economically. During the period of high wind generation when load

demand can be met by wind generation alone, hydro units can be shutdown and water

stored in the upper reservoir. This stored water can be used to generate electricity and

2

meet the load demand during the period of low wind generation. However, there is a

limitation due to the stochastic nature of river inflow. The extent to which a hydro plant

can effectively balance the wind power variation usually depends on its storage capacity

and river inflow. In a power system dominated by thermal power generation, wind

integration is a problem due to the ramping rate limitation on the thermal generators.

Even when there is abundant wind power, the thermal generators may at times have to be

operated at a non-optimal operating point which makes it uneconomical.

Pumped Hydroelectric Energy Storage (PHES) facilities have been considered an

attractive alternative for load balancing and energy storage. They can provide ancillary

services at high ramp rates, and they can also provide benefits from intraday energy price

variation by releasing energy at high demand periods and buying energy at off-peak

periods to pump water into the upper reservoir.

1.1.1 Overview of New Brunswick Power System

The New Brunswick Electricity Market is a physical bilateral market for

injections and withdrawals at the boundaries of the electric power transmission system in

the province of New Brunswick. The market is built upon the foundation of Federal

Energy Regulatory Commission (FERC) Order 888 open access transmission tariff. The

New Brunswick System Operator (NBSO) is the main interface between the market

participants and directs the operation and maintains the adequacy and reliability of the

transmission grid. It is also responsible for economic dispatch of generating units based

on the schedule and bid-in costs submitted by the owners of generating units while

maintaining system security by providing enough reserves.

3

The provincial government in 2004 adopted a Renewable Portfolio Standard

(RPS) of 10% by 2016. At present, 295 MW of wind power is already integrated. This

constitutes 6.70 % of the total capacity which is an indication of a rapid growth in wind

energy capacity. Canada Wind Energy Association (CanWEA) indicated that the

province of New Brunswick should increase its RPS target up to 20 per cent by 2020.

This would result in adding an increment of about 1,000 MW of wind power into the

province’s electricity mix [11].

The larger part of the New Brunswick power system energy mix is thermal

generation with 57.36 %. The remainder consists of 21.01 % hydro generation, 14.93 %

nuclear generation and 6.70 % wind generation [13]. At present, NBSO uses hydro

facilities to balance wind energy which is the cheapest option available. The cost of

balancing wind variation is estimated to be 0.5 to 2 cents/kWh of wind generation. As

stated earlier, the extent to which a hydro plant can effectively balance the wind power

variation will depend on its storage capacity and river inflow. All the hydro power plants

in New Brunswick power system are low head plants. This means that these generators

require more water to produce the same electric power than would be required by the

hydro generators of high head plants. In this context all the reservoirs of these hydro

power plants have short term storage capacity ranging from a day to a week. Adding to

this constraint is the fact that the inflow of the Saint John River is the major source of

water for the hydro plants. The inflow is in excess during the months of April and May,

and then reduces drastically in other months of the year. The capacity factor of the hydro

power plants on Saint John River is about 40 to 45 %.

4

Unfortunately, there is only one more site on the Saint John River itself for

expansion of hydro power capability. Wind balancing with available hydro generation

capacity is already constrained by its storage capacity and river inflow. The conventional

thermal units have ramp rate constraints. Therefore, integration of more wind would

require the province to depend on neighboring provinces for balancing wind generation.

This includes Hydro Quebec for additional power when there is a shortage of wind power

and New England for load when there is excess of wind generation [3].

Demand side management is actively being investigated as a means of following

wind power. If the load can be shifted based on the availability of wind, the intermittent

nature of wind will not be a problem for large scale wind integration. The investigation in

this area is being done through the PowerShift Atlantic Research Project in partnership

with Natural Resources Canada through the Clean Energy Fund, New Brunswick Power,

Saint John Energy, Maritime Electric, Nova Scotia Power, New Brunswick System

Operator, the University of New Brunswick, the Government of New Brunswick and the

Government of Prince Edward Island [21].

1.2 Literature Review

1.2.1 Brief History of Pumped Hydroelectric Energy Storage

Use of PHES started as early as 1890 in Italy and Switzerland. The majority of

plants were built from 1960s to the late 1980s. This was due to a rush for nuclear energy

after the oil crises in the early 1970s. PHES development in the United States and

European countries closely correlated to the nuclear development. PHES was used as a

5

system tool to supply energy at times of high load demand and to allow base load nuclear

units to operate in their base load mode during low load demand period. However, in

countries with rich hydro energy and no nuclear, PHES was developed primarily to

enhance the operation and efficiency of large scale hydro power plants. In addition PHES

also provided power system management capabilities such as balancing, frequency

stability and black starts [4].

The innovative idea of incorporating PHES into the New Brunswick electric

power system has been explored only once, way back in the year 1966 [15]. A PHES unit

was proposed on the Little River, with the Grand Falls head pond as its lower pool. It was

proposed to raise the Grand Falls head pond dam by 19.54 feet from its existing level of

427.26 feet above sea level and then extending the dam to cut off the Little River. The

main objective of the PHES was to store water during the months when the inflow of the

Saint John River at Grand Falls was more than the generating capacity of the Grand Falls

hydro units. The excess water which would otherwise be spilled from the Grand Falls

head pond would be pumped into the upper pool of the Little River PHES, the stored

water would then be optimized for the rest of the period until the river inflow was high

again. Raising the Grand Falls head pond as proposed would require some resettlement of

people living nearby the head pond and therefore it is not practical anymore. This would

also cause the head water from the Grand Falls dam to move across the US border which

would invite complicated cross-country boundary issues. Moreover, this study was

carried out way before the integration of wind into the power system was initiated and

has nothing to do with balancing the wind power.

6

More recently there has been a renewed interest in PHES as an integrator for

variable wind power. The idea that the intermittency of wind power can be smoothed

with hydro power is not new. While conventional hydropower plants can be used for

balancing wind power variation, there are limitations imposed unless the power plant has

very large reservoirs for long term storage of water. With more and more wind power

being integrated to the grid on a large scale, PHES is considered as the most suitable

method of balancing the wind power variability.

1.2.2 Benefits of Pumped Hydroelectric Energy Storage for Wind Integration

The benefits of adding wind power to the power system can be summarized as in

the following: 1. Reduction in overall generation cost as less fuel is consumed in

conventional power plants and 2. Reduction in carbon emission as less fossil fuel is

burned. However, due to the inherent variability of wind, increased wind power

integration may create negative impacts on the power system reliability. These negative

impacts may demand an increase in the cost of maintaining the same level of power

system reliability, also known as wind integration cost. In addition, such negative impacts

may offset the benefits of wind power and become significant as more wind power is

integrated into the power system [10]. It is important to assess these potential negative

impacts to ensure that they offset only a small part of the benefits. There are numbers of

studies completed on partnering PHES with wind as a means to mitigate wind variability

problem. A few benefits of PHES in regard to wind power integration as a result of these

studies are discussed here.

7

PHES is often partnered with wind farms to maximize the profit. At times of low

energy price the wind farms, instead of selling their power to the grid, can be used to

pump water from a lower reservoir and store in the upper reservoir. Whenever the energy

price increases above a certain threshold level, stored water is released back into the

lower reservoir producing electricity which is sold to the grid. Wind power is also sold to

the grid during this period of high energy price. In Alberta, in anticipation to 700 MW of

wind power in the near future a model which included a 40 MW Castle River wind farm

and a 40 MW PHES at Oldman dam was proposed. The result shows that while wind

power generation on its own was profitable, the profitability of wind power generation

increased by a factor of four when it was coupled with PHES [5].

PHES is also widely used in isolated regions to exploit wind power rejection, that

is available wind energy which cannot be used. The electricity generation in the Island of

Lesbos located in the North-Eastern part of the Aegean Sea is based mostly on thermal

power plants. The Island has quite a significant wind power potential but only a few sites

have been harnessed so far. Moreover, the annual energy consumption from wind farms

is only about 10 % of its installed capacity indicating heavy wind power rejection.

Incorporation of PHES into the power system of an isolated region improved wind power

rejection considerably. It has been shown that the renewable energy sources contribution

increased by 9 % from the current situation reaching 19 % of the Island’s energy balance

[6].

In developed countries with a deregulated energy market wind farms, when

partnered with PHES, allow greater operational flexibility and can be a means to

maximize their profitability by participating in the Day Ahead Market (DAM). In the

8

United States, with RPS of 20% by 2030, integration of wind power is on an increasing

trend. These wind farms, when partnered with PHES, could use PHES as a storage and

commitment balancing mechanism. This provides greater certainty to the wind operator’s

commitment process in the DAM and therefore to the grid. The wind farm’s profits from

participation in the energy market when partnered with PHES increase many fold with

the ability to fulfill commitments made on the DAM [7].

PHES can be financially beneficial even in a hydro dominated power system. In

British Columbia almost 90 % of the electricity is from hydro. PHES was proposed at

Mica-Revelstocke reservoir system with the objective to investigate its potential benefits

under different wind power development scenarios in the BC Hydro system. The

simulation results show that the incorporation of PHES in the system provided additional

economic benefits, which tend to increase with the increase in integrating wind power.

The wind power integration costs were seen to be reduced, and that was an incentive for

integrating additional wind power into the BC Hydro system. The incorporation of PHES

into the system also reduced water spillage from hydro power plants [8].

1.3 Motivation

Use of PHES to manage wind power variability is a growing trend all over the

world. There are a multitude of completed research studies on use of PHES for

integrating wind power. All these studies, or at least the ones referred to, indicate

significant benefits of incorporating PHES in the power system. However, case studies

conducted in different countries are not easy to compare due to different methodologies

9

and data used, as well as different assumptions on the availability of interconnection

capacity. Countries and power systems are different in how the variability and

unpredictability of wind power will impact the allocation and use of reserves, as well as

costs incurred [10].

The power system and energy market of the province of New Brunswick are

unique as compared to any other power system with regard to its energy mix,

interconnection with neighboring provinces, and deregulated energy markets. In order to

promote wind integration in the province, wind farms are paid a higher energy tariff and

no restrictions are imposed on their power generation. They are allowed to generate

electricity as and when wind is available without having to purchase any of the energy

reserves for power system reliability. It is the responsibility of NBSO to maintain the

system reliability by increasing energy reserve. The incremental energy reserve has to be

managed by the generating units of NB Power, which results in increased production

cost.

The province is identified for as high as 5500 MW of favorable wind power sites

[3]. If the province were to harness the full wind power capacity and integrate to the grid,

the production cost increment of the power system can be very significant. With no sites

available for new development of hydro power plants in the province, and with it not

being feasible to extend the storage for existing hydro power plants, there has to be an

alternative for a cheaper means of balancing the wind variability. PHES has proved to be

a good partner for wind farms to manage power variability. If PHES sites could be

identified in the province of New Brunswick and the benefits of incorporating it in the

10

power system turns out to be quite significant, then it may take integration of wind power

in the province to the next level.

1.4 Objectives of the Thesis

The objective of this thesis is to examine PHES sites in the province of New

Brunswick and investigate the advantages of incorporating it into the electric power

system of the province. This thesis aims to address the following points.

1. To identify the site and investigate the technical and financial feasibility of

building a PHES system in New Brunswick.

2. To develop an optimization model for investigating the benefits of incorporating

PHES into the New Brunswick power system. The model proposed seeks to

minimize the total generation cost.

11

Chapter 2

PUMPED HYDROELECTRIC ENERGY STORAGE

2.1 Overview

Pumped Hydroelectric Energy Storage system is one of the methods for

hydroelectric power generation that stores energy in the form of potential energy of water

in an upper reservoir, pumped from a second reservoir at a lower elevation. During

periods of high electricity demand, the stored water is released through turbines in the

same manner as a conventional hydro station. Excess energy, usually at lower cost during

the night and on weekends, is used to recharge the reservoir by pumping the water back

to the upper reservoir. Reversible pump/turbine and motor/generator assemblies act as

both a pump and a turbine.

There are two basic types:

1. Pure (or off-stream) PHES relies entirely on water that has been pumped into an

upper reservoir as their means of storing energy.

2. Combined PHES, also called pump-back power plants, uses a combination of

pumped water and natural stream flow to store/release energy.

Regarding equipment characteristics, PHES may take any of the three possible

configurations:

1. Four units: A separate pump coupled to a motor and a turbine coupled to a

generator. This configuration occupies a large amount of space and is no longer

used.

12

2. Three units: A pump and turbine are both coupled to a single reversible

motor/generator. The efficiencies of the pump and turbine can be optimized and

multi-stage pumps can be used for very high heads.

3. Two units: A reversible pump/turbine is coupled to a reversible motor/generator.

This configuration takes up a smaller space compared to the other two and has a

lower installation cost. However, the disadvantage is a decrease in the efficiency.

More than 95% of the PHES today in the world are of this type.

The PHES system turnaround/cycle efficiency is defined as the ratio between the energy

supplied while generating and the energy consumed while pumping. This efficiency

depends on both the pumping efficiency (ηp) and the generation efficiency (ηg). The

turnaround efficiency of any PHES system (ηh) is given as the product of pumping

efficiency and generation efficiency i.e.

ηh=ηp×ηg (2.1)

The turnaround efficiency usually ranges between 70-85%. PHES can be brought online

within 90 seconds and can be functioning at full power within 120 seconds. It can also

switch from pumping to generation or from generation to pumping mode in 180 to 240

seconds [8].

In this thesis, only the off-stream type PHES is considered and any description or

points mentioned hereafter are specific to this type.

2.2 Desirable Site Characteristics

Generally, the site for construction of a PHES should be hill or a mountain. The

upper reservoir is on top of the hill, the lower reservoir is at the bottom and the power

13

house with machineries can be in between the two but nearer to the lower reservoir.

There has to be enough space on the hill top as well as at the bottom of the hill for storage

of water. For the cost-effective construction of PHES, the site should have the following

characteristics:

1. Geologic conditions should be suitable for water-tight reservoirs.

2. Head, i.e. the vertical distance between the upper reservoir and the lower

reservoir, should be as high as possible. For a given power plant, the reservoir

storage requirement and the capacity of the water conduit are inversely

proportional to head. Therefore, the cost of reservoir and water conduit is greatly

reduced if the site has a high head.

3. Length of water conduit (intake tunnel, penstock, and discharge tunnel) should be

as short as possible. This is particularly important for the sites with lower head.

The economic limit for length of water conduit is a function of head and can be

expressed in terms of total length to head (L/H) ratio. The maximum acceptable

L/H ratio range is from 10 to 12 for high-head sites (360 m and above) and about

4 to 5 for low-head sites (150-180 m).

4. Reservoir sites (both upper and lower) should require minimum excavation and

embankment.

5. Power station should be located reasonably close to load centers or transmission

corridors.

14

2.3 Identification of PHES sites in New Brunswick

While it is desirable to have a site that has all the characteristics mentioned in

Section 2.2, it is not always possible. The province of New Brunswick, being almost at

the sea level, with flat terrain and porous rock filled land, there are no PHES sites that

would fulfill all the desired aforementioned characteristics. However, there are a few sites

in the province which would, with little modification and additional work, serve a good

site for PHES. One such site has been identified at Annie’s Mountain which is located at

45° 58´ N and 67 ° 29 ´ W as shown in Figure 1.

Figure 1: Site Identified for Construction of a 20 MW PHES Unit [26]

Proposed Upper Reservoir at

Elevation 250 m asl

Proposed Lower Reservoir at

Elevation 50 m asl Proposed

Power House

15

This is south of Woodstock, New Brunswick, where the Eel River flows into the

Saint John River. The upper reservoir is located at 250 m above sea level (asl) and the

lower reservoir located at 50 m asl, giving a gross head of 200 m. This can be classified

under low head PHES. Figure 2 shows the landscape of the site identified for

construction of PHES.

Figure 2: Proposed Site for PHES, Eel River and Annies Mountain

2.3.1 Upper Reservoir

The upper reservoir of PHES is proposed at the top of Annie’s Mountain. The

mountain has a crest of 270 m with a suitable storage contour at 250 m. The surface has a

length of 600 m and a width of 350 m. A reservoir with a dimension of length 250 m,

width 150 m and depth 15 m is proposed to be constructed. This would require

excavating the land surface to get a depth of 15 m. The upper reservoir will have a gross

16

storage capacity of 0.57 million cubic meter of water. In order to prevent the loss of water

from the reservoir through seepage, a lining would be required, which is an additional

cost.

2.3.2 Lower Reservoir

The lower reservoir of PHES is proposed at the bottom of Annie’s Mountain, by

intercepting the Eel River that flows into the Saint John River. There is already a

reservoir formed due to back water of Saint John River from the Mactaquac dam so the

lower reservoir requires little or no additional work. However, to ensure that there is

enough storage even at times when water level at the Mactaquac dam is drawn too low,

some excavation at the site is required. This is a great economic benefit of the PHES site

as the lower reservoir only involves very little construction cost.

2.3.3 Power House

The power house would be located towards the end of the water conduit near the

lower reservoir. The power output of the reversible pump-turbine set is expressed by the

following set of equations, where the symbols are defined after each equation.

Rated power output from generator

�� = �� ∗ � ∗ � ∗ � ∗ � (2.2)

Pg = rated power output in kW

ηg = generator efficiency (approximately 0.90)

ρ = density of water (approximately 1000 kg/m3)

g = acceleration of gravity (9.8 m/s2)

17

Qg = rated discharge from turbine in m3/s

Hg = rated generating head in m

The minimum draw down level of the upper reservoir is 240 m asl and therefore

the minimum head is 190 m. The effective storage of the upper reservoir that can be used

to generate electricity is therefore 0.375 million cubic meter (i.e. 250 x 150 x 10).

It is proposed to install a single reversible pump-turbine with a rated capacity of

20 MW. Using equation 2.2, the rated discharge from the turbine at rated head, rated

power output and generator efficiency of 0.9 can be calculated to be 11.34 m3/s. The

upper reservoir has the storage capacity to generate rated power output continuously for 9

hours.

In pumping mode, the power required to pump the rated discharge into the upper

reservoir is given by:

�� = (�� ∗ � ∗ � ∗ �)/� (2.3)

Pp = power required to pump rated discharge in kW

Qp = rated pump discharge in m3/s

ηp = pump efficiency

Hp = pumping head in m

It is assumed that the water level of lower reservoir is always maintained at 50 m

asl by the back water from the Mactaquac dam. Using equation 2.3, the water that can be

pumped into the upper reservoir from the lower reservoir at rated capacity, average head

of 195 m and assuming pump efficiency at 0.9 is 9.5 m3/s. The pump can be operated

18

continuously for 11 hours to pump back water from the lower reservoir, provided that the

water level at the upper reservoir starts at minimum.

2.3.3.1 Machine Characteristics

The machine characteristics of the proposed PHES are given below:

Station capacity: 20 MW (Single reversible pump-turbine unit)

Rated head: 200 m

Maximum head: 204 m

Minimum head: 190 m

Generator efficiency: 0.9

Pump efficiency: 0.9

Overall efficiency: 0.81

Rated discharge:

Generator mode: 11.34 m3/s

Pump mode: 9.5 m3/s

19

Figure 3: Proposed 20 MW PHES in New Brunswick at Annies Mountain

2.3.4 Water Conduit

The total length of water conduit connecting the lower reservoir through the

pump-turbine to the upper reservoir is 675 m. The horizontal distance between the upper

and lower reservoir is 200 m, the L/H ratio is 3.4, which is within the required range.

2.4 Capital Cost Estimate

The cost related to the construction of a PHES unit varies and depends on many

factors such as pipeline requirements, valves, gates, terrain, transportation, reservoir

construction, pump and generator requirements, power house structures, transmission

line, substation requirement and environmental protections etc. Construction cost

estimates a range from $1500 to $2500 per kW [24]. The cost also depends on the

location of the construction. Table 1 lists a number of new PHES projects around the

world, along with the estimated cost per kW for each PHES facility [23].

20

Table 1: Some Worldwide PHES facilities under construction

Project Location Capacity (MW)

Capital Cost (Million $)

Cost per kW ($/kW)

Baixo Sabor Portugal 171 484 2830

Limmern Switzerland 1000 1770 1770

Nant de Drance Switzerland 600 950 1583

Average 590.33 1068 2061

For the purpose of investigating the benefits of incorporating a PHES unit in New

Brunswick, a capital cost of 2500 $/kW is considered which is the higher side of the

worldwide accepted range.

2.5 Summary

A technically feasible site for construction of a PHES facility was identified at

Annie’s Mountain which is south of Woodstock, New Brunswick. The mountain has a

suitable contour at 250 m elevation where the upper reservoir with a total storage

capacity of 0.57 million m3 is proposed. The lower reservoir is proposed at the bottom of

the mountain at 50 m elevation which is already formed by the back water of the Saint

John River from the Mactaquac dam.

A single unit, reversible pump-turbine type with 20 MW rated capacity for both

generating and pumping mode is proposed for the PHES unit. A 675 m long penstock

connects the upper and the lower reservoirs through the power house. For the purpose of

calculating the payback period for construction of the PHES facility, a capital cost of

2500 $/kW is assumed.

21

Chapter 3

POWER SYSTEM OPERATION OPTIMIZATION

3.1 Details of Power System Generating Units

Most of the power systems include thermal generating units, hydro generating

units and wind farms. The following discusses the details of these units.

3.1.1 Thermal Units

a) Fuel Cost

Thermal units are represented by an input/output (I/O) curve which is normally

expressed in a quadratic form as shown below.

���(��) = �� + �� ∗ �� + (��)� ∗ �� (3.1)

FCi(Pi) is the fuel cost of the generating unit i, Pi is the power generation of unit i and ai,

bi, ci are cost coefficients of unit i which are either obtained from design calculations or

from heat rate tests. Figure 4 shows the ideal input-output characteristic curve of a

thermal unit.

Another important characteristic of a thermal unit is the incremental cost rate

which is the derivative of the I/O characteristics. The incremental cost rate is widely used

to make decisions on economic dispatching of the thermal units.

22

Figure 4: Classical Fuel Cost Curve of a Thermal Generator

b) Start-Up Costs

The temperature and pressure of a thermal unit has to be moved gradually. Fuel is

consumed to bring the temperature and pressure of the unit to the required level without

any power output. The fuel consumed prior to synchronization is termed as the start-up

cost. The start-up cost of a thermal unit depends on how long it has been off-line and can

vary from a maximum cold-start value to a much smaller value if the unit was only turned

off quite recently and the temperatures and pressures are still relatively close to normal.

3.1.2 Hydro Units

Hydro units are of two types, run-of-the-river i.e. without any storage capacity

and the ones with storage. The power output of run-of-the-river hydro plant which

23

depends entirely on the river inflow is inflexible and therefore cannot be optimized. Since

the fuel is free of cost, these units are always committed and dispatched first. For those

hydro plants with storage capacity, the output power from these units can be optimized

accordingly to offset thermal generation costs.

3.1.3 Wind Farms

The power output of wind turbines in a wind farm depends on the availability of

wind. Other than the operation and maintenance cost involved wind is free of cost. Wind

farms are committed and dispatched on an ‘as and when available’ basis.

3.2 Problem Explanation and Formulation

The objective of this thesis is to investigate the benefits of incorporating PHES

into a practical power system which consists of thermal units, a nuclear unit, hydro units

and wind farms. The approach used considers the benefits of a PHES unit in terms of

energy storage on a daily cycle, pumping energy into the storage during off-peak hours to

be used during peak load hours so that operation of expensive units are avoided.

Given the objectives of this thesis, it is considered that there is no curtailment of

wind power. The wind farms are always committed first, and only after scheduling the

remaining thermal and hydro units takes place. In order to simplify the problem, a perfect

wind power forecast is considered.

The hydro units with storage capacity are used to offset thermal generation costs

by storing water during off-peak load and using it to generate power at times of peak load

demand. They are however subjected to water resource constraint and depending on their

24

storage capacity, they can be classified as a daily, weekly, monthly or yearly hydro unit.

The available storage along with the natural river inflow has to be optimally used to

displace the maximum possible thermal unit generation cost over the study period. It is to

be noted that the hydro units do not cause direct fuel cost. Their operation nevertheless,

has an impact on the total fuel costs in the system.

Considering a power system consisting of I thermal units, J hydro units, K PHES

units and L wind farms, it is required to determine the operating status and

generating/pumping levels of all units over a time period T. The objective is to minimize

the system generation cost subject to system constraints and other unit constraints. The

problem is formulated as the following mixed integer programming problem [27].

Minimize:

∑ ∑ ���(��) ∗���� ��(�)

���� + ��� ∗ {��(�) ∗ (1 − ��(� − 1))} (3.2)

FCi (Pi) is the fuel cost ($/h) of thermal unit i

Ui (t) is the status of thermal unit i at period t (1 if unit is ON and 0 if unit is OFF)

CSi is generator start-up cost ($) of thermal unit i and

T is the total time period which is 8760 hours.

Subject to the following constraints:

a) Load/Generation Balance Constraint

This constraint requires that at each scheduled period, the total generation must be

equal to the sum of total load demand (losses are neglected).

25

∑ ��(�)���� + ∑ �$(�)

%$�� + ∑ (�&

�(�) −'&�� �&

�(�)) +∑ �((�)

)(�� = *(�) (3.3)

Pi(t), Pj(t), Pl (t) are the power output (MW) of thermal unit i, hydro unit j and wind farm

l at period t.

Pkg (t) is the power output (MW) of PHES unit k at period t

Pkp(t) is the pump load (MW) of PHES unit k at period t and

D (t) is the total system demand (MW) at period t

b) Spinning Reserve

Unanticipated loss of a generating unit or an interconnection causes unacceptable

frequency drop if not corrected. This requires increased generation from other units to

keep the frequency drop within acceptable limits. Rapid increases in production are only

possible if all committed units are not operating at their maximum capacity. Spinning

reserve provides this make-up generation and is described for any time period as the total

amount of generation available from all units synchronized to the grid minus the load

demand plus the transmission line losses.

Spinning reserve requirements can differ from one power system to another.

However, the typical rule is to set it equal to the generation of the largest capacity unit

online at any given period or to set as a percentage of the total load demand.

∑ �+�,�(�) − ��(�)���� +∑ �+�,$(�) − �$(�)

%$�� +∑ �+�,&

�(�) −'

&��

�-�(�)≥�//(�) (3.4)

Pmaxi(t), Pmaxj(t), Pmaxl(t) are the maximum output capacity (MW) of thermal unit i,

hydro unit j and the PHES unit k at period t

26

Pmaxkg(t) is the maximum output capacity (MW) of the PHES unit k at period t

SRR(t) is the spinning reserve requirement (MW) at period t

c) Maximum Ramp Up/Down Constraint:

To avoid damaging the turbines, the electrical output of a thermal unit cannot

change by more than a certain rate.

Maximum ramp up constraint

��(� + 1) −��(�) ≤ 1/�� (3.5)

Maximum ramp down constrain

��(�) −��(� − 1) ≤ 1/*� (3.6)

MRUi is the maximum ramp up (MW/min) of thermal unit i

MRDi is the maximum ramp down (MW/min) of thermal unit i

d) Minimum Up Time (MUT):

This constraint requires that the unit should stay ON for a minimum number of

hours once it is started.

23456�6677��8�9:���6+965�98;�<�, (��(�) − ��(� − 1)) > 0,

∑ ��(�)@A�BC�

D�E ≥ 1�F� (3.7)

MUTi is the minimum up time (hr) of the thermal unit i

e) Minimum Down Time (MDT):

Likewise, this constraint requires that the unit should stay OFF for a minimum

number of hours once it is shutdown.

27

23456�6677ℎ4� − :HI5���6+965�98;�<�, (��(�) − ��(� − 1)) < 0,

∑ (1 − ��(�)@K�BC�D�E ≥ 1*F� (3.8)

MDTi is the minimum down time (hr) of thermal unit i

f) Unit Capacity Constraint:

This constraint puts a restriction on the power output level of the generating unit.

Once the unit is put ON, its power output must always be between the operating ranges of

the generating unit i.e. between its minimum stable level and the output maximum

capacity.

1�L� ≤ ��(�) ≤ �+�,� (3.9)

1�L$ ≤ �$(�) ≤ �+�,$ (3.10)

1�L( ≤ �((�) ≤ �+�,( (3.11)

�+65&�(�) ≤ �&

�(�) ≤ �+�,&�(�) (3.12)

�+65&�(�) ≤ �&

�(�) ≤ �+�,&�(�) (3.13)

MSLi, MSLj, MSLl are the minimum stable limit (MW) of thermal unit i, hydro unit j and

wind farm l

Pmaxkg(t) is the maximum output capacity (MW) of PHES unit k at period t

Pminkg(t) is the minimum stable limit (MW) of PHES unit k at period t

Pmaxkp(t) is the maximum pump load (MW) of PHES unit k at period t

Pminkp(t) is the minimum pump load (MW) of PHES unit k at period t

28

g) Hydro Unit Energy Constraint:

The output energy of a hydro unit is limited by its river inflow and the storage

capacity of its head pond. The hydro units are represented as energy constrained units.

During seasons when the inflow is high, in addition to the maximum energy constraint

the head pond can store, there has to be a minimum energy constraint in order to avoid

spillage of water. Weekly hydro energy constraint unit is expressed as below.

M+65$(I99-) ≤ M$(I99-) ≤ M+�,$(I99-) (3.14)

Eminj(week) is the minimum energy (MWh) in a week that must be released from the

storage of hydro unit j to avoid spillage

Emaxj(week) is the maximum energy (MWh) in a week that can be released from the

storage of hydro unit j

Ej(week) is the actual energy generation (MWh) in a week for hydro unit j

h) PHES Unit Energy Constraint

The PHES operation is also limited by the size of its head pond and its lower

reservoir. The storage capacity of both reservoirs is expressed in terms of energy (MWh)

and it has to be within the maximum and the minimum limits.

M+65& ≤ M&(�) ≤ M+�,& (3.15)

The head pond level dynamics are expressed as

29

Generating mode:

M&(� + 1) = M&(�) − �&�(�) (3.16)

Pumping mode:

M&(� + 1) = M&(�) + (�&�(�) ∗ 0.81) (3.17)

Emink is the minimum energy storage (MWh) requirement for storage of PHES unit k

Emaxk is the maximum energy storage capacity (MWh) of the head pond of PHES unit k

Ek(t) is the stored energy in head pond of PHES unit k at period t

3.3 Solution Method

The problem statement contains a large number of both continuous variables

(generation level) and discrete variables (unit ON/OFF status) in both objective and

constraint functions. This problem belongs to the class of Mixed Integer Programming

(MIP) problems. MIP methods and codes are available and applied to many engineering

problems. The most common method is the Branch and Bound (B&B) algorithm, which

is described in the following section.

3.3.1 Branch and Bound Algorithm

B&B algorithm is a general search method. In order to describe the B&B

algorithm, the following need to be defined:

• Predecessor

• Successor

30

Problem Pj is the predecessor to problem Pk and problem Pk is the successor to problem

Pj. These problems are identical except that one continuous-valued variable in problem Pj

is constrained to be an integer in problem Pk.

In the B&B method, the first step is to solve the predecessor problem Pj. If the

solution Xj results so that all integer variables are indeed integer, the problem is solved.

On the other hand, if it results in a solution that contains a non-integer variable, a

successor problem Pk is constructed by indirectly imposing the continuous-valued

variable to be an integer. The value and the objective are then checked for its feasibility

and optimality by exploring the entire solution space, which is achieved by branch and

bound at each solution node.

There are two central ideas in the B&B method.

1. Branch: It uses the linear programming relaxation to decide how to branch. Each

branch will add a constraint to the previous linear programming relaxation in order to

enforce an integer value on one variable that was not an integer in the predecessor

solution.

2. Bound: It maintains the best integer feasible solution obtained so far, as a bound on

tree-paths that should still be searched.

a. If any tree node has an objective value less optimal than the identified bound, no

further searching from that node is necessary, since adding constraints can never

improve an objective.

b. If any tree node has an objective value more optimal than the identified bound,

then additional searching from that node is necessary.

31

3.4 Software for Implementation

There are many commercial software packages available in the market for solving

power system operation optimization problem. An academic version of PLEXOS for

Power Systems, a product of Energy Exemplar Ltd is used in this thesis [12].

It is a powerful power system optimization tool and can be used for a wide array

of power system studies including 1. Power system operation and planning 2. Market and

transmission analysis and 3. Long term resource and transmission planning. For the

purpose of this thesis, only the unit commitment and economic dispatch parts under the

operation and planning application are used. This software is also used widely in research

work, in both the academic and commercial areas [25].

PLEXOS for Power Systems can be integrated with the best and fastest

mathematical programming solvers such as MOSEK, Xpress-MP, CPLEX and Gurobi.

The advantage of using PLEXOS for Power Systems is that it gives the freedom to

choose between any solvers to solve the MIP problem. Gurobi Optimizer 4.6.1 is used as

the solver in this thesis as its academic license was available [22].

3.5 Summary

The objective of this chapter is to describe the models used to investigate the

benefits of incorporating the PHES unit into the power system consisting of a nuclear

unit, thermal units, hydro units and wind farms. It is a unit commitment and economic

dispatch problem with inclusion of a PHES unit in the power system. The objective

function is to minimize the total generation cost of the system over a horizon of one year,

subjected to the various system and units constraints.

32

For the purpose of modeling and simulation, PLEXOS for Power Systems, a

product of Energy Exemplar Ltd is used in this thesis. It is a very powerful power system

optimization tool using the Mixed Integer Programming (MIP) method to formulate the

objective function. It is very user friendly and can be integrated with four different

powerful solvers. The Gurobi Optimizer is used in this thesis, which is a MIP solver

employing the Branch and Bound Algorithm.

33

Chapter 4

INPUT DATA AND ASSUMPTIONS

The power system considered in this thesis consists of 24 generating units. Unit 1

is coal fired, 2 - 6 are oil units, 7 - 12 are diesel units, 13 is a nuclear unit, 14-17 are

natural gas units, 18 – 21 are hydro units, 22 and 23 are wind farms and 24 is a PHES

unit. The details of the generating units of the practical power system are given in Table I

of Appendix A. Data used to define each generating unit and the assumptions made for

simulation studies in this thesis are discussed in this chapter.

4.1 Defining Thermal Units

Thermal generators are modeled by defining their maximum/minimum capacity

(name plate), rating (operating range), input-output curves, MUT, MDT, ramp rates, start

cost, running cost, its initial status (ON or OFF), initial power generation and number of

hours the unit has been ON or OFF.

The input-output characteristics of the units were obtained from the thesis work of

Kenneth Scott Brown [18]. The fuel cost characteristics of NB Power thermal units were

used for optimization of energy supply cost with emission quota. The fuel cost

characteristics of all thermal units were based on the fuel cost forecast of year 2000 from

which the true heat rate characteristics of each units were calculated using the fuel cost

values of the year 2000.

The machine capacity and ratings were obtained from the NBSO 10-year Outlook

Report [16]. The MUT, MDT, unit start cost, unit running cost and minimum stable limit

34

of each thermal unit were obtained from the thesis work of Yun (Nancy) Huang [18]. The

generating units owned by NB Power were used to solve the security constrained unit

commitment problem.

The values for maximum ramp up/down limit of each thermal unit are based on

the Electricity Outlook Project report for NBSO [19].

4.2 Defining Hydro Units

Hydro units are defined as energy constrained unit which means that their

generation depends on the reservoir capacity each is connected to and the river inflow

which is seasonal. Most hydro units have an annual capacity factor ranging from 30 % to

50 %. The river inflow data of hydro plants were obtained from the web site of

Environment Canada [20]. This data is shown in terms of monthly average MW

generation in Table 2.

Table 2: Monthly Average River Inflow of Hydro Units

Year Month Monthly Average Generation (MW)

Unit 18 Unit 19 Unit 20 Unit 21

2010 June 50 103 50 30

2010 July 20 61 20 15

2010 August 20 70 20 15

2010 September 30 214 30 25

2010 October 40 216 30 25

2010 November 40 238 30 25

2010 December 50 244 30 25

2011 January 30 120 30 20

2011 February 30 118 30 20

35

2011 March 50 233 40 20

2011 April 100 602 60 40

2011 May 100 345 60 40

All the hydro power plants in the province have a short term storage capacity of

approximately 48 hours. This means that without any natural inflow into the head pond,

the hydro units can operate at their maximum output capacity continuously for 48 hours

given that the head pond was at its maximum level initially.

During the period of very high inflow, even though there is enough water for a

hydro unit to operate at its rated output capacity, the generation is limited below its rated

capacity due to the significant rise in the tail pool level. This is also taken into account

while modeling the hydro units.

The hydro units are also required to generate some minimum power during high

river inflow period to avoid spillage. This is also taken into account while modeling

hydro units in the software.

4.3 Defining Wind Farms

For the purpose of investigating the benefits of incorporating PHES into the

power system of New Brunswick, a perfect wind forecast is assumed so that the

comparison of the simulation results of two cases with and without PHES are not biased

by the wind energy output which is represented as free energy in this model.

It is to be noted that the uncertainty of wind power forecast has a great impact on

unit commitment and dispatch. However, the deterministic wind power data with

increased reserve requirement showed similar result

data [14]. In this thesis, to take care of load forecast and wind forecast error, load

following reserve is taken into account

power data of two Atlantic wind farms

thesis and the data is shown in Figure 5

4.4 Defining PHES unit

A 20 MW reversible pump

efficiency of 81 % is used which is within the globally accepted efficiency r

to 85 %. This implies that for every unit of generation 1.23 units of energy is required to

36

increased reserve requirement showed similar results as that of a stochastic wind power

]. In this thesis, to take care of load forecast and wind forecast error, load

following reserve is taken into account which is described in section 4.6

power data of two Atlantic wind farms were used for the purpose of simulation in this

the data is shown in Figure 5.

Figure 5: Hourly Wind Power Output Data

Defining PHES unit

20 MW reversible pump-turbine is proposed in this thesis. The round

efficiency of 81 % is used which is within the globally accepted efficiency r

to 85 %. This implies that for every unit of generation 1.23 units of energy is required to

a stochastic wind power

]. In this thesis, to take care of load forecast and wind forecast error, load

is described in section 4.6. Hourly wind

were used for the purpose of simulation in this

turbine is proposed in this thesis. The round-trip

efficiency of 81 % is used which is within the globally accepted efficiency range of 75 %

to 85 %. This implies that for every unit of generation 1.23 units of energy is required to

37

pump the required water back to the head pond. It is a closed loop PHES with no outflow

of water from the system. The upper reservoir has a maximum storage capacity of 275.5

MWh and its minimum permissible storage is 91.85 MWh. The storage volume of upper

and lower reservoirs is required to be recycled to its initial value at the end of every

week. This is achieved by imposing a hard constraint on the storage end volume and

setting a weekly target equal to its initial value. Table 3 shows the characteristic of PHES

unit.

Table 3: Characteristics of the PHES Unit

Un

it

Max

Cap

acity

(M

W)

Min

Sta

ble

Leve

l (M

W)

Ru

nni

ng C

ost

($/h

r)

Sta

rt C

ost

($)

Max

Ram

p U

p

(MW

/min

.)

Max

Ram

p D

ow

n (M

W/m

in.)

Pu

mp

Effi

cien

cy

(%)

Pu

mp

Load

(M

W)

Min

Pu

mp

Load

(M

W)

24 20 7 0 0 20 20 81 20 7

4.5 System Load Data

To further simplify the model, a deterministic load data is used for the purpose of

simulation in this thesis. Advanced software is already out in the commercial market

which gives a very accurate load forecast. The hourly load data of New Brunswick for the

year 2010-2011shown in Figure 6 is used for the purpose of simulation in this thesis.

Figure 6:

4.6 System Reserves

To maintain system reliability, the generating units are required to provide system

reserve at any given time

are considered for this simulat

that generation capacity maintained for one reserve can also be used for

reserves and vice versa.

1) Spinning Reserve

A minimum of

Except for the nuclear unit and wind farm

reserve provided that they are committed.

38

: Hourly Load Data of New Brunswick for 2010

tain system reliability, the generating units are required to provide system

reserve at any given time in order to accommodate contingencies. Three types of reserves

are considered for this simulation. All these reserves are non-exclusive

that generation capacity maintained for one reserve can also be used for

reserves and vice versa.

Spinning Reserve

A minimum of 140 MW is reserved to overcome any generator contingency.

uclear unit and wind farms, all other generators are able to offer

reserve provided that they are committed.

Hourly Load Data of New Brunswick for 2010-2011

tain system reliability, the generating units are required to provide system

contingencies. Three types of reserves

exclusive of each other so

that generation capacity maintained for one reserve can also be used for the other two

0 MW is reserved to overcome any generator contingency.

generators are able to offer this

39

2) Regulation Reserve

A minimum of 10 MW is reserved both for regulation up and regulation down

reserve to meet the minute to minute change in system frequency.

3) Load Following Reserve

The load following reserve is maintained to follow the changes in load. It is

dynamic meaning that it changes every hour according to how the load changes in that

interval. The calculation/forecast of hourly load following reserve requirement from

hourly load forecast data and hourly wind farm output power data is detailed below.

L�/(�) = (P9�LH�:(� + 1) − P9�LH�:(�))/2 (4.1)

NetLoad(t) is calculated using the expression:

P9�LH�:(�) = *(�) − ∑ �((�))(�� (4.2)

4.7 Transmission Line Losses

All the generators and the loads are considered connected to the same bus which

means that the transmission system losses and line congestions are ignored in the

simulation of the practical system model.

4.8 Summary

The power system considered in this thesis consists of 24 generating units. The

thermal units are defined using their maximum output capacity, minimum stable limit,

fuel cost characteristics, MUT, MDT, ramp rates, start cost, initial status, initial

generation and the time it has been ON or OFF. The hydro units are defined with their

40

storage capacity and river inflow in addition to the unit capacity details. The PHES unit is

defined with its overall efficiency, pump load and storage capacity.

Deterministic hourly load data of New Brunswick for the year 2010-2011 is used

to define the load. Similarly wind power output data of two Atlantic wind farms for the

same year was used to define the wind farms. System reserve requirements of the power

system are defined with spinning reserve, regulation reserve and load following reserve.

For simplicity of the model, a single bus system is considered. This means that all

the load and generators are connected to the same bus. Therefore, transmission losses and

transmission line congestions are ignored in this study.

41

Chapter 5

RESULTS AND ANALYSIS

5.1 Details of Test System Model

The modeling of a simple test system consisting of only 4 units is conducted for

the purpose of giving an idea how the software solves the given optimization problem.

The test system modeled for this purpose consists of four units, a coal unit, hydro unit,

wind farm and a PHES unit. The details of the test system are given in Table 4 below.

Table 4: Characteristics of Test System Units

Units Coal Unit

Hydro Unit

Wind Farm

PHES Unit

No of Units No. 1 1 1 1

Max Capacity MW 400 100 30 50

Min Stable Level MW 50 30 0 10

Heat Rate Base GJ/hr 1069.36

Heat Rate Incr1 GJ/MWh 22.105

Heat Rate Incr2 GJ/MWh² 0.0048

Start Cost $ 1100 0 0 0

Min Up Time Hrs 5

Min Down Time Hrs 4

Initial Generation MW 100

Initial Hours Up Hrs 8

Initial Hours Down Hrs 0

Pump Efficiency % 75

Pump Load MW 50 Min Pump Load MW 10

The hydro uni

102.48 GWh and the energy constraint

shown in Figure 7.

Figure 7: Monthly Average

The PHES unit of the test system is considered

maximum storage capacity of 74 GWh.

PHES unit are considered to be at 75 % of thei

recycled back to initial storage volume at the end of the simulation period.

Hourly wind power ou

farm.

42

ydro unit of the test system is considered to have a

and the energy constraint is defined by the average month

onthly Average Natural Inflow for Hydro Unit of Test System

PHES unit of the test system is considered a closed loop system and has a

maximum storage capacity of 74 GWh. The initial storage of both the hydro unit and the

PHES unit are considered to be at 75 % of their maximum storage capacity and are

ed back to initial storage volume at the end of the simulation period.

Hourly wind power output data as shown in Figure 8 was used to model the

of the test system is considered to have a storage capacity of

defined by the average monthly natural inflows

for Hydro Unit of Test System

a closed loop system and has a

The initial storage of both the hydro unit and the

maximum storage capacity and are

ed back to initial storage volume at the end of the simulation period.

was used to model the wind

Figure 8:

The hourly system load used for simulation of the tes

MW and a valley of 87

43

: Hourly Wind Power Data of Test System Wind Farm

The hourly system load used for simulation of the test system

MW and a valley of 87 MW. The hourly load data for one year is shown in Figure 9

Figure 9: Hourly Load Data of Test System

of Test System Wind Farm

t system has a peak of 421

one year is shown in Figure 9.

5.2 Results for Test System Model

The simulation was run over a time horizon of

hour. Two cases were considered,

PHES unit included in the system.

5.2.1 Total Generation Cost of the System

Figure 10 shows the total generation cost

the Base Case and Case

significant reduction in

Figure 10

44

Test System Model

The simulation was run over a time horizon of one year with

. Two cases were considered, Base Case without the PHES unit

ES unit included in the system.

ration Cost of the System

shows the total generation cost on a monthly basis

the Base Case and Case 1. The inclusion of PHES unit into the system

significant reduction in the overall generation cost over a period of one year.

10: Total Monthly Generation Cost of the Test

one year with an interval of one

out the PHES unit, and Case 1 with the

on a monthly basis of the test system for

he inclusion of PHES unit into the system results in

of one year.

Test System

The only unit contributing to generation

quadratic function. Inclusion of PHES

system as it is a net consumer,

thermal unit. Figure 11

Base Case and Case 1.

Figure 11

45

unit contributing to generation cost is the coal unit

Inclusion of PHES results in an increase in total

as it is a net consumer, but it reduces the total generation cost

Figure 11 shows the unit wise generation in a block of one

1.

11: Weekly Unit Wise Generation of the Test System

is the coal unit, whose fuel cost is a

total generation of the

generation cost by peak shaving the

ock of one week for the

of the Test System

Figure 10 shows

of June through September

active operation of PHES unit during th

5.2.2 Operation of PHES Unit

In order to avoid using hydro energy to pump water, a condition was impo

the PHES unit. Figure 12

unit. The PHES unit never operated

operation i.e. generating.

Figure 12: Hourly Net Generation

PLEXOS for Power System

on the energy price. This is done by p

46

shows significant savings in terms of generation cost

ptember, when the load is low. These savings are contributed by the

active operation of PHES unit during these months as shown in Figure 11

Operation of PHES Unit

avoid using hydro energy to pump water, a condition was impo

the PHES unit. Figure 12 shows the hourly operation of the hydro unit and the PHES

PHES unit never operated in pumping mode when the hydro unit

operation i.e. generating.

Hourly Net Generation of Hydro Unit and PHES Unit

for Power System optimizes the operation of PHES unit by arbitraging

This is done by pumping water into the upper pond when the energy

in terms of generation cost during the months

savings are contributed by the

in Figure 11.

avoid using hydro energy to pump water, a condition was imposed on

ydro unit and the PHES

the hydro unit was in

of Hydro Unit and PHES Unit of Test System

optimizes the operation of PHES unit by arbitraging

umping water into the upper pond when the energy

price is low and generating it when the price is high. Operation of PHES unit with respect

to energy price is shown in

Figure 13: Hourly

The purpose of running a test system model was to build confidence in the

functioning of the software package

dispatch problem of the test system

a stepping stone to move ahead with the large practical system.

5.3 Results of Practical System

The simulation

compare the benefits of incorporating PHES into the power sys

first scenario, 6.7 %

47

price is low and generating it when the price is high. Operation of PHES unit with respect

to energy price is shown in Figure 13.

Hourly Net Generation of PHES Unit and Energy Price

The purpose of running a test system model was to build confidence in the

of the software package. The solutions of the unit commitment and economic

dispatch problem of the test system are in line with the early expectations.

a stepping stone to move ahead with the large practical system.

Practical System Model

The simulation of the practical system was run for three different

compare the benefits of incorporating PHES into the power system

wind integration was considered which re

price is low and generating it when the price is high. Operation of PHES unit with respect

rice of Test System

The purpose of running a test system model was to build confidence in the

. The solutions of the unit commitment and economic

the early expectations. This provides

was run for three different scenarios to

tem for each case. In the

which represented the present

48

actual scenario of the province’s power system. In the second scenario, 10 % wind

integration was considered in anticipation that the province would achieve its RPS target

of 10 % by the year 2016. In the third scenario, 20 % wind integration was considered

which represented the large scale wind integration report target for 2020 [3]. Each

scenario had two cases, one without a PHES and the other with a PHES unit.

For all the scenarios, the model was configured to undertake a year (hourly

interval) of optimization starting June 2010 until May 2011 with one week look-ahead

period of one hour resolution. The simulation proceeded by solving these steps in

chronological sequence. The model was solved by using the Gurobi solver with a relative

gap set to 1 % and the maximum time for search set to 230 seconds.

The upper reservoirs of all the hydro units were considered to be at 75 % of their

maximum storage capacity initially and a hard constraint to recycle back to its initial

volume at the end of each month was imposed.

5.3.1 Total Generation Cost of the System

Figure 14 shows the monthly generation cost of the system for the three scenarios

without the inclusion of PHES unit. There was always a decrease in generation cost every

month when wind integration to the system was increased. In general, one could expect a

proportionate decrease in generation cost given that there was a proportionate increase in

wind integration. This was not true for the power system of New Brunswick. There was

significant decrease during the months of November, December, January and February

which were characterized by high system load demand. Otherwise, during the months of

low load demand, especially during April, associated with high river inflow, the

reduction in system generation cost was

Figure 14: Month Wise Generation Cost

With the inclusion of

reduction in generation cost for each level of wind integration.

total generation cost of the system

Table 5: Savings in

Scenario

Without

With PHES

Saving (Thousand $)

49

especially during April, associated with high river inflow, the

ion in system generation cost was minimal.

onth Wise Generation Cost of the System without PHES Unit

With the inclusion of a PHES unit in the power system there was a

reduction in generation cost for each level of wind integration. Table 5

total generation cost of the system and the savings for each scenario.

Savings in Total Generation Cost of the Practical System

Scenario Annual Total Generation Cost (Thousand $)

6.7 % Wind 10 % Wind

260297.1617 239835.37 185641.1263

259327.5564 238417.335 184757.3679

Saving (Thousand $) 969.6053 1418.0343

especially during April, associated with high river inflow, the

the System without PHES Unit

nit in the power system there was a further

Table 5 shows the annual

cenario.

Total Generation Cost of the Practical System

Annual Total Generation Cost (Thousand $)

20 % Wind

185641.1263

184757.3679

883.7584

Figure 15: Month Wise Total Generation Cost of the

50

: Month Wise Total Generation Cost of the Practical System

Practical System

51

Figure 15 shows the month wise total generation cost of the system for different

scenarios. In each scenario, there was a significant saving in generation cost during the

month of January which was the month with highest system load demand and relatively

low river inflow.

With 10 % wind integration, it was beneficial to have a PHES unit throughout the

year, while for 6.7 % and 20 % wind integration, having a PHES unit in the month of

December and February respectively cost more to generate. This shows that operation of

PHES unit during these months was not economical.

A 20 MW capacity PHES unit looks to be the optimal size for the 10 % wind

integration as the benefit of incorporating the PHES unit in the system is the highest with

this scenario as compared to the other two. The savings in system generation cost

decrease as wind integration is increased to 20 %.

5.3.2 Effect of PHES Unit in System Generation

A PHES unit having a round-trip efficiency of only 81 % is a net consumer of

energy and the total generation of the system increases with inclusion of PHES. Table 6

shows the energy required to pump and the energy generated by PHES unit in each

scenario.

Table 6: Total Generation and Pump Energy of PHES Unit

Scenario 6.7 % Wind 10 % Wind 20 % Wind

Energy Required for Pumping (GWh)

15.0421374 17.9832921 25.364558

Generation From PHES (GWh) 12.1829163 14.5651766 20.5592919

Net Generation (GWh) -2.85922115 -3.41811549 -4.80526606

52

The operation of the PHES unit increases with increase in wind integration level.

This must be due to the increased variability that comes with increased wind integration.

Inclusion of the PHES unit into the power system reduces generation from

expensive diesel and oil units or inefficient coal unit, while increasing generation from

the cheap natural gas units. Table 7 shows the total generation from each category of

generators for different scenario.

Table 7: Category Wise Total Generation from Practical System Units

Category 6.7 % Wind 10 % Wind 20 % Wind

Without PHES

With PHES

Without PHES

With PHES

Without PHES

With PHES

Diesel Unit (GWh)

8.66 5.58 7.76 4.69 6.07 5.29

Oil Unit (GWh)

609.33 606.79 511.60 510.68 304.86 302.90

Coal Unit (GWh)

1857.36 1851.74 1750.56 1746.69 1384.67 1368.65

Nuclear Unit (GWh)

5562.60 5562.60 5562.60 5562.60 5562.60 5562.60

Natural Gas Unit (GWh)

2307.28 2320.64 2190.47 2199.95 1849.32 1860.81

Hydro Unit (GWh)

2825.20 2825.19 2828.24 2825.24 2822.98 2823.43

Wind Farm (GWh)

705.93 706.68 1025.13 1029.93 1945.89 1957.53

Inclusion of a PHES unit also improves the wind power dispatch. Figure 16 shows

the monthly generation of wind farms for the three scenarios. There is a significant

increase in wind power dispatch when a PHES unit is included in the system especially

during the month of April when hydro units are base loaded due to very high river inflow.

During this month, the PHES unit uses any excess wind power to pump water which

would otherwise be curtailed as

hydro generation, nuclear and any next cheap unit having the capability to provide system

reserve.

Figure 16: Monthly Total

5.3.3 Operation of PHES Unit in the Power System

The simulation was run for 8760 hours. The 365 values of pump energy

consumed were averaged for Hour 1. This was repeated for all 24 Hours.

shows the average pump energy consumed by the PHES unit for each hour

period. There is a similar pattern for all the t

unit operates to pump water into the upper reservoir past midnight until 6 AM every day

which are the hours of low load. During this low load period, the amount of water

pumped also increases proportionally with the increase in wind integration level.

53

otherwise be curtailed as the system load requirement would have been met

hydro generation, nuclear and any next cheap unit having the capability to provide system

: Monthly Total Generation from the Wind Farm for Different Scenario

Operation of PHES Unit in the Power System

The simulation was run for 8760 hours. The 365 values of pump energy

consumed were averaged for Hour 1. This was repeated for all 24 Hours.

average pump energy consumed by the PHES unit for each hour

There is a similar pattern for all the three levels of wind integration. T

unit operates to pump water into the upper reservoir past midnight until 6 AM every day

the hours of low load. During this low load period, the amount of water

pumped also increases proportionally with the increase in wind integration level.

would have been met by

hydro generation, nuclear and any next cheap unit having the capability to provide system

for Different Scenarios

The simulation was run for 8760 hours. The 365 values of pump energy

consumed were averaged for Hour 1. This was repeated for all 24 Hours. Figure 17

average pump energy consumed by the PHES unit for each hour over a day’s

hree levels of wind integration. The PHES

unit operates to pump water into the upper reservoir past midnight until 6 AM every day,

the hours of low load. During this low load period, the amount of water

pumped also increases proportionally with the increase in wind integration level.

54

Figure 17: Operation Pattern of PHES Unit in Pumping Mode for Practical System

The operation of the PHES unit in pumping mode perfectly complements the

system load pattern shown in Figure 18. The load begins to peak from 7 AM until noon

and again from 6 PM until 9 PM. The PHES unit operates in pumping mode during the

off peak hours of load.

Figure 18: Yearly Average System Load Pattern of the Practical System

0

1

2

3

4

5

6

7

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Ye

arl

y A

ve

rag

e P

um

p L

oa

d (

MW

)

No of Hours

6.7% Wind

10% Wind

20% Wind

1200

1300

1400

1500

1600

1700

1800

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Ye

arl

y A

ve

rag

e L

oa

d (

MW

)

Hours

Load

55

5.3.4 Summary

The hydro units were modeled with short term storage capacity of only 48 hours.

This did not provide much flexibility in terms of hydro-thermal coordination as the water

available during low load could not be stored and later used during peak load months.

The hydro generation could only be optimized over a period of one week which indicated

that the available stored energy needed to be utilized optimally within that period.

Inclusion of PHES in the system did affect the operation of hydro units but the effect was

not very significant. The benefits in generation cost were from the ability of the PHES

unit to arbitrage on the energy price over a day/week period.

Inclusion of 20 MW capacity PHES unit in the system resulted in reduced system

generation cost over a period of a year for different wind integration levels. However, the

reduction reached its optimum with 10 % wind integration and started decreasing with

further increase in wind integration. The inclusion of PHES unit also improved wind

power dispatch. The wind power dispatch increased in proportion to the increase in wind

integration level.

Considering the capital cost of the PHES unit at $ 2500/KW ($ 1500/KW), the

total construction cost of the PHES unit is $ 50,000,000.00 ($ 30,000,000.00). For the

scenario with 6.7 % wind integration with a net annual saving of $ 969,605.50, the

project payback period without considering interest rates or depreciation is 52 years (31

years). For 10 % wind integration, the saving improves to $ 1,418,034.00 and the

payback period reduces to 35 years (21 years). For the last scenario with 20 % wind

integration, the saving reduces to merely $ 883,758.00 for which the payback period

increases to 57 years (34 years).

56

Chapter 6

CONCLUSIONS

6.1 Conclusions

The analysis of PHES effects on the power system of New Brunswick can provide

the following conclusions.

a) The practical power system was modeled using the PLEXOS for Power Systems and

solved with the Gurobi solver. The model without PHES unit was executed within

three hours and when adding PHES unit the execution time increased one more hour.

While solving this model, the relative gap in the Gurobi solver was set at 1% (default

setting is at 0.1 %), this greatly improved the execution time but at the cost of

accuracy of the optimal solution. However, it was a reasonable tradeoff since for 0.1

% relative gap, the execution time tended to go to infinity (the simulation run was

stopped after one day run).

b) There could be a few more possible PHES sites along the Tobique River in the Blue

Mountains. The PHES site at Annie’s Mountain is accessible by road and therefore it

is possible to visit the site to study its technical feasibility for actual construction of a

PHES system. The most favorable feature of the PHES site at Annie’s Mountain is

the naturally existing lower reservoir, formed by backwater from the Mactaquac dam.

c) The simulation result showed reduction in generation cost of the system with an

increase in wind integration level. The reduction was more significant during the

months of high load demand than those with the low load demand. This related to the

57

fact that during low load cheap energy from the nuclear unit and hydro units alone

were able to meet the load demand.

d) When the PHES unit was included, there was further reduction in the generation cost

of the system in each scenario of wind integration. The reduction in system

generation cost was highest with 10 % wind integration indicating that the 20 MW

capacity PHES unit was an optimal size for 10 % wind integration level.

e) The inclusion of the PHES unit increased generation from cheap natural gas units,

while at the same time reduced generation from expensive diesel, oil and coal units.

This also related to the fact that the PHES unit would pump during off peak load

hours using cheap energy, when cheap units along with cost-free units were able to

meet the system load. The PHES unit would then generate during peak load hours,

when expensive units normally had to be run to meet the system load, thus displacing

energy from expensive units.

f) The province of New Brunswick has a RPS target of 10% wind integration by 2016.

Based on this commitment from the province, the results of this simulation can be

related to this level of wind integration. Financial feasibility analysis of PHES unit

indicates 35 years payback period with 10 % wind integration level. This is not an

attractive return as such, but considering a 50 to 75 years life span of the PHES

facility 35 years payback period is a considerable benefit. Moreover, there are other

benefits of incorporating PHES into the system, which are foregone in this research.

These benefits, to name a few, include revenue from providing reserves and revenue

from trading carbon credits in carbon trading markets.

58

6.2 Recommendations for Future Work

a) This thesis has explored the feasibility of PHES site in the Annie’s Mountain. There

are other possible sites along the Tobique River in the Blue Mountains. These sites

may be studied for their technical feasibility for construction of PHES.

b) In this thesis only, a 20 MW capacity PHES unit has been considered, since this is the

maximum capacity that can be harnessed from the identified site. The benefit with

different capacities of the PHES unit has not been investigated in this thesis.

However, after identifying more feasible PHES sites, the system can be modeled and

benefits investigated for different capacity of PHES unit.

c) For the purpose of investigating the benefits of incorporating a PHES unit in the

system, the benefits only in terms of savings in total generation cost of the system

have been considered using a deterministic model of the system. The model can be

extended to include benefits of PHES in terms of wind integration cost. For this

purpose, a stochastic model has to be used for which there is provision in PLEXOS

for Power Systems. In this thesis, emission constraints on fossil fuel units have not

been modeled which leaves room for future study to see whether the benefits increase

with emission constraints on thermal units.

d) In this thesis, the Gurobi solver has been used to solve the optimization problem.

There are different MIP solvers and their performances differ depending on the type

of problems. Other solvers can be tested to compare the accuracy of results and the

execution time.

59

e) PLEXOS for Power Systems is a powerful optimization software which has a

multitude of options to allow users to customize their models. While modeling the

test system, a constraint has been imposed on the PHES unit that has prevented it

from pumping when the hydro unit is in operation. When this constraint is removed,

the software is free to optimize the operation of PHES unit. Simulation runs of the

two models have given different generation costs. The results of both simulation runs

with and without the constraint are provided in Table 8.

Table 8: Total Generation Cost of Test System with and without Constraint

Conditions Total Generation Cost (Thousand $)

Without PHES With PHES

Without Constraint 85918.8192 84418.3694

With Constraint 85918.8192 84533.8321

The hydro units of New Brunswick power system have a short term storage

capacity. They are operated on a weekly cycle meaning that the reservoir level is recycled

back to maximum level at the start of every week and then optimized for rest of the week.

In order to make the hydro units of the practical system closely represent this operation, a

hard constraint (end volume storage = monthly target) has been introduced in the model

to recycle back the storage to its initial value at the end of every month. For the purpose

of investigating the effect of a small change in modeling, another simulation run has been

performed, but with a yearly target instead of a monthly target. Despite the fact that the

pattern of results has been similar, there has been quite an appreciable difference in the

obtained values. This is given in Table 9.

60

Table 9: Total Generation Cost of Practical System with Different Storage Targets

Conditions Savings in Generation Cost (Thousand $)

6.7 % Wind 10 % Wind 20 % Wind

Storage Recycled Monthly 969.6053 1418.0343 883.7584

Storage Recycled Yearly 496.6715 1276.091 889.6888

The data of Table 9 show that simulation results are very sensitive to small

changes or modifications in the modeling. Given the complications involved with

PLEXOS for Power Systems, comparing the results with other power system

optimization software can be a good approach before finalizing the results obtained from

one single optimization tool.

61

REFERENCES

[1] J.F. Manwell, J.G. McGowan and A.L. Rogers, “Wind Energy Explained, Theory,

Design and Application”, John Wiley & Sons Ltd, 2009.

[2] Web pages: http://www.nbso.ca/Public/en/op/market/about.aspx

[3] Ea Energy Analysis, “Large Scale Wind Power in New Brunswick - A Regional

Scenario Study Towards 2025”, Prepared for New Brunswick System Operator and

New Brunswick Department of Energy, August 2008.

[4] J.P. Deane, B.P. O Gallachoir, E.J. McKeogh, “Techno-Economic Review of

Existing and New Pumped Hydro Energy Storage Plant”, Renewable and

Sustainable Energy Reviews, Volume 14, 1293–1302, 2010.

[5] Trevor J. Nickel, “An Economic Model for Wind Generated Electricity in Alberta

Using Pumped Storage for Supply Management”, Natural Resources and Energy,

University of Alberta School of Business, 2005

[6] M. Kapsali, J.K. Kaldellis, “Combining Hydro and Variable Wind Power

Generation by Means of Pumped-Storage Under Economically Viable Terms”,

Applied Energy, Volume 87, 3475-3485, 2010.

[7] Christine Schoppe, “Wind and Pumped-Hydro Storage: Determining Optimal

Commitment Policies with Knowledge Gradient Non-Parametric Estimation”,

Princeton University, June 2010.

[8] Humberto Andres Rivas Guzman, “Value of Pumped-Storage Hydro for Wind

Power Integration in the British Columbia Hydroelectric System”, MScE Thesis,

University of British Columbia, June 2010.

62

[9] Edgardo D. Castronuovoa, Joao A. Pecas Lopes, “Optimal Operation and Hydro

Storage Sizing of a Wind–Hydro Power Plant”, Electrical Power and Energy

Systems, Volume 26, Pages 771–778, 2004.

[10] Hannele Holttinen, “Estimating the Impacts of Wind Power on Power Systems-

Summary of International Energy Agency (IEA) Wind Collaboration”,

Environmental Research Letters, Volume 3, 2008.

[11] Canada Wind Energy Association (CanWEA), “CanWEA’s Submission to New

Brunswick Energy Commission”, March 2011, http://www.gnb.ca/Commission/

pdf/CanWEA-NBEnergyCommission_final.pdf.

[12] Web pages: http://www.energyexemplar.com

[13] NB Power, “Annual Report of NB Power”, 2007/2008.

[14] Jianhui Wang, Audun Botterud, Vladimiro Miranda, Claudio Monteiro, Gerald

Sheble, “Impact of Wind Power Forecasting on Unit Commitment and Dispatch”,

http://www.dis.anl.gov/pubs/65610.pdf.

[15] Ronald Weston Hudson, “Optimization of Reservoir Operation for Pumped Storage

Hydro Development”, MScE Thesis, UNB, 1966.

[16] NBSO, “10 Year Outlook: An Assessment of the Adequacy of Generation and

Transmission Facilities in the New Brunswick 2011-2021”, May 2011.

[17] Kenneth Scott Brown, “Optimization of Energy Supply Costs with Emissions

Quotas”, MScE Thesis, UNB, December 1994.

[18] Yun (Nancy) Huang, “Security Constrained Unit Commitment Under the

Deregulated Environment”, MScE Thesis, UNB, April 2000.

63

[19] Hatch Limited, “Electricity Outlook Project Report - Part 1”, Released for NBSO,

August 2011.

[20] Web Pages: http://www.wateroffice.ec.gc.ca

[21] Web Pages: http://powershiftatlantic.com/overview.html

[22] Web Pages: http://www.gurobi.com/

[23] Elizabeth A. Ingram, “Worldwide Pumped Storage Activity”, Hydro Review

Worldwide, Pages 12-20, September 2010.

[24] Charles J. Murray, “Beyond the Smart Grid: Utilities Will Still Need Electric

Storage” Design News, Volume 65, Issue 6, Page 31, June 2010.

[25] Web Pages: http://energyexemplar.com/news/publications/

[26] Web Pages: http://atlas.nrcan.gc.ca/site/english/maps/topo/map/

[27] Allen J. Wood, Bruce F. Wollenberg, “Power Generation Operation & Control”,

John Wiley & Sons, 1984.

64

APPENDIX A

Table 10: Characteristics of Thermal Units of Practical System Model

Un

its

Ma

xim

um

Cap

aci

ty (

MW

) M

inim

um S

tabl

e

Le

vel (

MW

)

He

at R

ate

Bas

e

(GJ/

hr)

He

at R

ate

Incr

. (G

J/M

Wh)

He

at R

ate

Incr

.2

(GJ/

MW

h²)

Run

nin

g C

ost

($/h

r)

Sta

rt C

ost

($

)

Min

Up

Tim

e

(hr)

M

in D

own

Tim

e

(hr)

M

ax

Ram

p U

p

(MW

/min

.)

Ma

x R

amp

Dow

n

(MW

/min

.)

Initi

al G

ene

ratio

n

(MW

) In

itia

l Ho

urs

Up

(hr)

In

itia

l Ho

urs

Dow

n (

hr)

1 480 175 1069.36 22.11 0.0048 3.2 22.9 4 6 16 16 175 10 0

2 350 80 329.49 12.49 0.0001 6.1 8.7 2 6 45 45 0 0 10

3 350 80 373.14 11.94 0.0001 6.1 8.7 2 6 45 45 0 0 10

4 350 80 409.82 11.39 0.0001 6.1 8.7 2 6 45 45 0 0 10

5 103 35 148.71 10.67 0.0001 6.1 5.1 6 6 13 13 0 0 10

6 215 85 193.55 11.06 0.0001 6.1 13.2 6 6 25 25 0 0 10

7 100 20 222.04 16.24 0.0001 7 1.5 0 1 20 20 0 0 10

8 100 50 222.04 16.24 0.0001 7 1.5 0 1 20 20 0 0 10

9 100 50 222.04 16.24 0.0001 7 1.5 0 1 20 20 0 0 10

10 100 50 222.04 16.24 0.0001 7 1.5 0 1 20 20 0 0 10

11 100 20 207.77 16.09 0.0001 7 1.5 0 1 20 20 0 0 10

12 29 3 104.11 12.29 0.0001 1.5 7 0 0 7 7 0 0 10

13 635 100 333.69 3.58 0 0.5 6.4 4 6 20 20 635 10 0

14 45 11 44.76 6.07 0.0001 2.2 3.1 6 6 6 6 20 10 0

15 102 30 62.12 4.84 0.0042 2.2 3.1 6 6 13 13 30 10 0

16 102 30 77.8 4.52 0.0061 2.2 3.1 6 6 13 13 30 10 0

65

Un

its

Ma

xim

um

Cap

aci

ty (

MW

) M

inim

um S

tabl

e

Le

vel (

MW

)

He

at R

ate

Bas

e

(GJ/

hr)

He

at R

ate

Incr

. (G

J/M

Wh)

He

at R

ate

Incr

.2

(GJ/

MW

h²)

Run

nin

g C

ost

($/h

r)

Sta

rt C

ost

($

)

Min

Up

Tim

e

(hr)

M

in D

own

Tim

e

(hr)

M

ax

Ram

p U

p

(MW

/min

.)

Ma

x R

amp

Dow

n

(MW

/min

.)

Initi

al G

ene

ratio

n

(MW

) In

itia

l Ho

urs

Up

(h

r)

Initi

al H

our

s D

own

(h

r)

17 61 15 76.8 8.07 0.0067 2.2 4.2 6 6 8 8 15 10 0

18 113 40

0 0

45 10 0

19 672 270

0 0

280 10 0

20 64 25

0 0

30 10 0

21 44 15

0 0

0 0 10

Curriculum Vitae

Name: Dorji Namgyel

University attended: University of Rajasthan

Rajasthan, India

Bachelor of Engineering

Electrical Engineering (2004)