pumped hydroelectric energy storage · PDF fileWind Following with Pumped Hydroelectric Energy...
Transcript of pumped hydroelectric energy storage · PDF fileWind Following with Pumped Hydroelectric Energy...
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)