Frequency Control on an Island Power
System
with Evolving Plant Mix
by
Gillian R. Lalor
A thesis presented to
The National University of Ireland
in fulfilment of the
requirements of the degree of
Philosophiae Doctor
in the
School of Electrical, Electronic and Mechanical Engineering
University College Dublin
September 2005
Supervisor of Research: Professor M.J. OMalleyNominating Professor: Professor A.M. de Paor
Abstract
Continual balancing of active power generated and consumed is vital for power system
security and stability, and to maintain frequency within an acceptable tolerance around
nominal system frequency. Due to the large size of individual generators with respect to
total system size, the loss of a generator in a small island system can cause a large power
imbalance, and consequently a significant frequency excursion. Low system inertia
results in high rates of change of frequency when a power imbalance occurs. Therefore,
system frequency control on an isolated power system is particularly challenging.
As the generating mix on a power system evolves, moving away from traditional steam
generating units, the behaviour of the power system in response to a power imbalance
also changes. Both combined cycle gas turbine (CCGT) and wind turbine generators
have distinctive effects on system frequency control. As each technology comprises an
increasing proportion of generation on power systems worldwide, a clear understanding
of the effects of CCGT and wind turbine generator characteristics on system frequency
control is required in order to maintain secure and stable power systems.
A dynamic model of the Ireland electricity system is developed, tuned and validated
for the purpose of studying short-term frequency control on an island system. Each
frequency responsive generating unit on the Ireland system is modelled using low order
models tuned to extensive data from frequency events on the Ireland system. The
system load is modelled using a single measurement based dynamic load model, which
incorporates the frequency sensitivity and inertial contribution of the load during power
imbalances. Frequency control through under-frequency load shedding is also incorpo-
rated in the model. The system model was subsequently validated through comparison
with frequency events not previously used for tuning. The resultant system model has
the ability to predict the under-frequency behaviour of the Ireland power system for
up to 20 seconds following a loss of generation with a very good level of accuracy.
i
The active power generated by a base loaded CCGT is coupled to system frequency. A
model suitable for studying the short-term dynamic response of a combined cycle gas
turbine to a system frequency deviation is developed. The model is tuned and validated
with event data from combined cycle gas turbines on the Ireland electricity system. This
model is used in conjunction with the validated system model to study the impact of
increasing levels of CCGT generation on short-term frequency control of a small island
system during a loss of generation event. Results indicate that as the number and
proportion of base loaded combined cycle gas turbines increases, frequency control
may become more challenging. The magnitude of the system frequency excursion
increases non-linearly as the proportion of base loaded CCGTs increases. Therefore, if
the number of CCGTs increases, large frequency excursions will become more likely and
transmission system operators may need to review their frequency control strategies to
maintain current security standards and to avoid the shedding of customers.
Increased system inertia is intrinsically linked to the addition of synchronous genera-
tion to power systems. However, due to differing electromechanical characteristics, this
inherent link is not present in wind turbine generators. Dynamic models of two differ-
ent wind turbine technologies are integrated into the validated system model, which
is modified to represent the predicted 2010 Ireland electricity system. The effect on
system frequency during a loss of generation event is examined for varying wind pene-
trations on the system. The results indicate that regardless of wind turbine technology,
the displacement of conventional generation with wind will result in increased rates of
change of system frequency. The magnitude of the frequency excursion following a loss
of generation may also increase. Amendment of reserve policies or modification of wind
turbine inertial response characteristics may be necessary to facilitate increased levels
of wind generation, particularly for an isolated power system.
In addition to the short-term dynamic effects of wind generation on frequency control,
longer-term effects as a result of the wind generation characteristics of variability and
unpredictability need to be taken into account in order to maintain adequate levels
of system security in all time frames. However, while a clear understanding of the
technical aspects of frequency control is vital to ensure system security, they comprise
just one part of the whole frequency control issue. The technical aspects therefore need
to be put in perspective by examining them as part of the broader picture, which also
includes economic consequences. With rapidly increasing wind generation on many
power systems, the effect on all aspects of frequency control is being examined in
ii
detail, to assess and quantify the impact of wind integration. A review of a number
of previous wind integration studies is carried out and a preliminary methodology
is proposed for examining the effects of wind integration on all aspects of frequency
control over a number of time-frames. Some illustrative results are given for a sample
AC interconnected system.
iii
Acknowledgements
I would like to thank everybody whose help and support contributed to this thesis. In
particular, there are some without whom this thesis would not have been possible:
Professor Mark OMalley, whose guidance, help, expertise and encouragement through-
out the project was invaluable. Always making time for discussion, his supervision
throughout has been excellent and I am extremely grateful for everything over the last
four years. Thank you.
Dr. Damian Flynn and Julia Ritchie, of the Queens University of Belfast, who collab-
orated on the development of the Ireland electricity system model and with whom I
had many useful and informative discussions.
Dr. Lawrence Jones of Areva T&D, who gave me the opportunity to to spend 3 months
working with Areva T&D in Bellevue, Washington.
Professor Chen Ching Liu of the University of Washington, Seattle, without whom the
trip to Washington would not have been possible.
Colleagues in ESB National Grid, for many useful discussions and interactions, in
particular Jonathan OSullivan, Michael Power, Doireann Barry, Kate OConnor, Pat
McGrath and John Kennedy.
ESB Power Generation, in particular Michael OMahony, Alan Egan and Nicholas
Tarrant, for information and advice during the development of the CCGT model.
Tom Wilson of Viridian, for help and useful discussions during the development of the
CCGT model.
Dr. Alan Mullane, for his guidance and expertise in collaboration on the study into
iv
frequency control and wind turbine technology. Also for all the advice and questions
answered, about LaTex as well as wind, and proof reading this thesis.
Ronan Doherty, with whom I collaborated on the study into frequency control in com-
petitive market dispatch in addition to a number of different projects, for the many
useful and informative discussions throughout.
All occupants of Room 157 over the course of the last four years. In particular, Shane
Rourke for his help, advice and the invaluable discussions since I started and Hugh
Mullany for his advice and proof reading this thesis. Also Tim Hurley, Andy Keane,
Eleanor Denny, Garth Bryans and Ciara OConner for the constant moral support, tea
and coffee breaks, and a enjoyable working atmosphere.
My family, Liz, Pamela, Richard, John, and in particular Mum and Dad. Thank you
for the constant support and encouragement, not just over the last four years, but in
everything I do.
All my friends, whose friendship I value greatly.
And finally James, for the endless encouragement, support, confidence in me and, not
least, patience, which have been invaluable over the last number of years. Thank you
for everything.
v
Publications arising from this thesis
Journal Papers:
R. Doherty, G. Lalor and M. OMalley,Frequency Control in Competitive Electricity
Market Dispatch, IEEE Transactions on Power Systems, August 2005, Vol. 20, No.
3, pp. 1588-1596. (Appendix C)
G. Lalor, J. Ritchie, D. Flynn, and M. OMalley, The Impact of Combined Cycle Gas
Turbine Short Term Dynamics on Frequency Control, IEEE Transactions on Power
Systems, August 2005, Vol. 20, No. 3, pp. 1456-1464. (Appendix B)
G. Lalor, A. Mullane and M. OMalley, Frequency Control and Wind Turbine Tech-
nologies, IEEE Transactions on Power System. In press, 2005. (Appendix D)
Conference Papers:
G. Lalor and M. OMalley, Frequency Control on an Island Power System with In-
creasing Proportions of Combined Cycle Gas Turbines, presented at IEEE Powertech
Conference, Bologna, June 2003. (Appendix E)
G. Lalor, J. Ritchie, S. Rourke, D. Flynn, and M. OMalley, Dynamic Frequency Con-
trol with Increasing Wind Generation, presented at IEEE Power Engineering Society
General Meeting, Denver, Colorado, June 2004. (Appendix F)
vi
Table of Contents
1 Introduction 1
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Frequency Control of an Island Power System . . . . . . . . . . . . . . 4
1.2.1 Frequency Control . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2.2 Island Power Systems . . . . . . . . . . . . . . . . . . . . . . . . 7
1.2.3 Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.3 The Aims and the Scope of this Thesis . . . . . . . . . . . . . . . . . . 12
2 System Model 14
2.1 The Ireland Power System . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.2 Modelling the Ireland Power System. . . . . . . . . . . . . . . . . . . . 16
2.2.1 Assumptions of the Model . . . . . . . . . . . . . . . . . . . . . 17
2.2.2 Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.2.3 Load . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.2.4 Connecting System . . . . . . . . . . . . . . . . . . . . . . . . . 32
2.3 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
2.4 Simulation Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
vii
2.5 Tuning the Ireland System Model . . . . . . . . . . . . . . . . . . . . . 35
2.5.1 Generating Units . . . . . . . . . . . . . . . . . . . . . . . . . . 36
2.5.2 Load Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
2.5.3 Connecting System . . . . . . . . . . . . . . . . . . . . . . . . . 44
2.6 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
2.6.1 Validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
2.6.2 Frequency Control in Competitive Electricity Market Dispatch . 46
2.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
3 Frequency Control with Combined Cycle Gas Turbines 53
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
3.2 CCGT Background and Characteristics . . . . . . . . . . . . . . . . . . 54
3.2.1 Gas Turbine Component . . . . . . . . . . . . . . . . . . . . . . 55
3.2.2 The Heat Recovery Steam Generator and Steam Turbine Com-ponents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
3.3 Literature review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
3.3.1 CCGT Modelling . . . . . . . . . . . . . . . . . . . . . . . . . . 63
3.4 CCGTs on the Ireland System . . . . . . . . . . . . . . . . . . . . . . . 65
3.5 CCGT Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
3.5.1 CCGT Model Structure . . . . . . . . . . . . . . . . . . . . . . 66
3.5.2 Model Tuning and Validation . . . . . . . . . . . . . . . . . . . 70
3.6 The Impact of CCGT Dynamics on Frequency Control . . . . . . . . . 75
3.7 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
3.8 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
viii
4 Frequency control and Wind Turbine Technology 81
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
4.2 Wind Generation Technology . . . . . . . . . . . . . . . . . . . . . . . 82
4.3 Wind Turbine Generator Modelling . . . . . . . . . . . . . . . . . . . . 86
4.3.1 Fixed Speed Wind Turbine Model . . . . . . . . . . . . . . . . . 86
4.3.2 DFIG Wind Turbine Model . . . . . . . . . . . . . . . . . . . . 89
4.4 Wind Generation on the Ireland Electricity System . . . . . . . . . . . 92
4.4.1 Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
4.4.2 Simulating Procedure . . . . . . . . . . . . . . . . . . . . . . . . 93
4.5 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
4.5.1 Response of wind turbine technologies to system frequency devi-ations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
4.5.2 System frequency control with increasing wind penetration . . . 95
4.5.3 Supplementary response from DFIG . . . . . . . . . . . . . . . . 100
4.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
5 Supplementary Study: Wind Integration Studies and Frequency Con-trol 105
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
5.2 Review of Wind Integration Studies . . . . . . . . . . . . . . . . . . . . 107
5.3 Preliminary Wind Integration Frequency Control Study . . . . . . . . . 114
5.3.1 e-terra simulator . . . . . . . . . . . . . . . . . . . . . . . . . . 115
5.3.2 Wind Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
5.3.3 Determination of Wind Variability Costs . . . . . . . . . . . . . 118
5.3.4 Determination of Wind Unpredictability Costs . . . . . . . . . . 121
ix
5.4 Preliminary Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
5.4.1 Available Wind Data . . . . . . . . . . . . . . . . . . . . . . . . 122
5.4.2 Scope of the study . . . . . . . . . . . . . . . . . . . . . . . . . 122
5.4.3 Sample Test System . . . . . . . . . . . . . . . . . . . . . . . . 123
5.4.4 Scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
5.4.5 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
5.5 Discussion and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . 130
6 Conclusions 134
6.1 Synopsis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
6.2 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
6.3 Scope for future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
References 140
A Frequency Disturbance Event 152
B The Impact of Combined Cycle Gas Turbine Short Term Dynamicson Frequency Control 155
C Frequency Control in Competitive Electricity Market Dispatch 166
D Frequency Control and Wind Turbine Technologies 176
E Frequency Control on an Island Power System with Increasing Pro-portions of Combined Cycle Gas Turbines 186
F Dynamic Frequency Control with Increasing Wind Generation 194
x
List of Figures
1.1 Operating reserve time-scales . . . . . . . . . . . . . . . . . . . . . . . 6
1.2 Recorded system frequency on Ireland electricity system . . . . . . . . 9
2.1 Generation mix on the Ireland electricity system for 1995, 2005 and 2010 15
2.2 Steam unit model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.3 Open cycle gas turbine model . . . . . . . . . . . . . . . . . . . . . . . 24
2.4 Linear hydroelectric-turbine model . . . . . . . . . . . . . . . . . . . . 28
2.5 Ireland system model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
2.6 Inertial response control loop . . . . . . . . . . . . . . . . . . . . . . . 37
2.7 Six frequency events on the Ireland system with corresponding poweroutput of a sample generator . . . . . . . . . . . . . . . . . . . . . . . . 38
2.8 Comparison between actual and simulated frequency response of a steamunit to a low frequency event . . . . . . . . . . . . . . . . . . . . . . . 40
2.9 Turlough Hill generating unit response for two low frequency events . . 42
2.10 Actual and simulated system frequency for a 267 MW generation loss . 46
2.11 Actual and simulated system frequency for a 277 MW generation loss . 47
2.12 Actual and simulated system frequency for a 381 MW generation loss . 48
2.13 Actual and simulated system frequency for a 201 MW generation loss . 49
2.14 Simplified system frequency model . . . . . . . . . . . . . . . . . . . . 50
xi
2.15 Comparison of the generation response of the black box model with thevalidated system model . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
3.1 Single-shaft CCGT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
3.2 Multi-shaft CCGT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
3.3 CCGT model structure . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
3.4 CCGT ambient temperature dependency . . . . . . . . . . . . . . . . . 71
3.5 CCGT ambient pressure dependency . . . . . . . . . . . . . . . . . . . 72
3.6 Change in power output of a typical near base loaded CCGT in responseto a frequency event on the system . . . . . . . . . . . . . . . . . . . . 73
3.7 Simulated power output of the GT component of a typical CCGT to afrequency drop of 0.5 Hz . . . . . . . . . . . . . . . . . . . . . . . . . . 74
3.8 Winter peak scenario with 422 MW trip . . . . . . . . . . . . . . . . . 77
3.9 Summer night valley scenario with 400 MW trip . . . . . . . . . . . . . 78
3.10 Summer day valley scenario with 400 MW trip . . . . . . . . . . . . . . 79
3.11 Sensitivity of system frequency nadir to increasing proportions of CCGTs 80
4.1 Typical Cp curve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
4.2 Fixed speed wind turbine Generator . . . . . . . . . . . . . . . . . . . . 84
4.3 Doubly fed induction generator . . . . . . . . . . . . . . . . . . . . . . 85
4.4 DFIG model with FOC controller . . . . . . . . . . . . . . . . . . . . . 91
4.5 Comparison of fixed speed WTG and DFIG WTG responses to the lowfrequency event . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
4.6 Effect of increasing wind penetration on maximum rate of change offrequency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
4.7 Simulated system frequency following the trip of largest infeed duringthe SDV scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
xii
4.8 Frequency nadir and static reserve tripped following the loss of thelargest infeed for increasing wind penetration during the Summer DayValley scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
4.9 Frequency nadir and static reserve tripped following the loss of thelargest infeed for increasing wind penetration during the Summer NightValley scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
4.10 Supplementary control loop for DFIG WTG controller. . . . . . . . . . 102
4.11 Comparison of fixed speed WTG and DFIG WTG responses to the lowfrequency event, including supplementary control loop . . . . . . . . . . 103
4.12 Simulated system frequency following the trip of largest infeed duringthe SDV scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
5.1 Test system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
5.2 Wind farm power output time series . . . . . . . . . . . . . . . . . . . 126
5.3 System frequency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
5.4 ACE: Control Area A . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
5.5 ACE: Control Area B . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
5.6 ACE: Control Area C . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
5.7 Generator power output: Control Area A . . . . . . . . . . . . . . . . . 131
5.8 Generator power output: Control Area B . . . . . . . . . . . . . . . . . 132
5.9 Generator power output: Control Area C . . . . . . . . . . . . . . . . . 133
A.1 Recorded system frequency on Ireland electricity system . . . . . . . . 152
xiii
List of Tables
2.1 Under-frequency setting for Turlough Hill operating modes . . . . . . . 28
4.1 Comparison of inertial response from various generators . . . . . . . . . 95
4.2 Maximum ROCOF following loss of largest infeed (422MW) for variousoperating scenarios, wind turbine penetrations and wind turbine tech-nology type. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
5.1 Test system generation capacity . . . . . . . . . . . . . . . . . . . . . . 123
5.2 Test system set-up . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
5.3 Test case scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
xiv
Nomenclature
a = Frequency sensitivity of GT exhaust gas flow calculation factor
A = Area swept by wind-turbine rotor (m2)
b = Constant, such that a+b=1
B = Frequency bias setting (MW/0.1Hz)
Cp = Performance coefficient
CD = Boiler drum integral coefficient (s)
CSH = Boiler superheater integral coefficient (s)
f = System frequency (Hz)
FA = Actual control area frequency (Hz)
fgen = Under frequency relay setting for Turlough Hill gen mode (Hz)
FHP = Fraction of power output from high pressure ST stage
fint = Under frequency relay setting for interruptible customers (Hz)
FIP = Fraction of power output from high pressure ST stage
FLP = Fraction of power output from high pressure ST stage
fmin = Under frequency relay setting for Turlough Hill min gen mode (Hz)
fo = Nominal system frequency (Hz)
fpump = Under frequency relay setting for Turlough Hill pump mode (Hz)
FS = Scheduled control area frequency (Hz)
fspin = Under frequency relay setting for Turlough Hill spin mode (Hz)
fUFLS = Under frequency load shedding relay setting (Hz)
G = Set of generators
Gw = Gate position (per unit)
i = Current (A)
igv = Inlet guide vane angle ()
Ij = Inertia of generating unit j (kgm2)
INT = Logical operator for inertial control loop
xv
J = Polar moment of inertia of wind turbine and rotor (kgm2)
K = Friction drop coefficient of orifice between drum and superheater
K1P = Proportional gain for d axis current controller
K2P = Proportional gain for q axis current controller
K1I = Integral gain for d axis current controller
K2I = Integral gain for q axis current controller
KBB1 = Black box model parameter 1
KBB2 = Black box model parameter 2
Ki = IGV controller constant
kpf = Steady state frequency sensitivity of the load
kpv = Active power and voltage load model parameter
kqf = Reactive power and frequency load model parameter
kqv = Reactive power and voltage load model parameter
Kscl = Supplementary control loop constant
KE = Kinetic energy (MWs)
KEi = Kinetic energy of generator i (MWs)
KEL = Kinetic energy of system load (MWs)
KEo = Kinetic energy at nominal frequency fo (MWs)
Ligv = Inlet guide vane position (per unit)
Lm = Per phase mutual inductance (H)
Lr = Per phase rotor inductance (H)
Ls = Per phase stator inductance (H)
L = L2
m LrLs (H)
m = Steam flow rate out of boiler drum (per unit)
ms = Steam flow rate into steam turbine (per unit)
mw = Steam flow rate into boiler drum (per unit)
N = System speed (per unit)
NG = Number of generators
Nref = Reference system speed (per unit)
NIA = Algebraic sum of the actual flows on all tie lines/interconnectors (MW)
NIS = Algebraic sum of the scheduled flows on all tie lines/interconnectors (MW)
p = Differential operator
P = Active power (MW)
Pa = Ambient pressure (mbar)
Paero = Accelerating aerodynamic power (MW)
xvi
PD = Boiler drum pressure (per unit)
Pelec = Electrical power (MW)
Pf = Number of machine poles
PGEN = Active power generated (MW)
Pk = Amount of generation lost (MW)
Pload = Active power required by the load (MW)
Pmax = Maximum rated generator power output (MW)
Pmech = Mechanical power (MW)
Pmin = Minimum rated generator power output (MW)
Po = Steady state system demand (MW)
Ppu = Active power (per unit)
PT = Boiler throttle pressure (per unit)
Q = Heat Energy (per unit)
Qload = Reactive power required by the load (MVAR)
R = Resistance ()
Rd = Droop (%)
Rr = Radius of rotor (m)
Rp = Primary reserve available at 5 seconds (MW)
SP = Generator operating set-point (per unit)
T1 = Load time constant (T)
Ta = Ambient temperature (C)
Tcd = Compressor discharge time constant (s)
TCH = Steam transport and conversion time constant (s)
TCO = Steam turbine crossover and conversion time constant (s)
Tem = Electromagnetic torque (N m)
Temref = Reference electromagnetic torque (N m)
Tgf = Gas fuel system time constant (s)
Ti = IGV controller integration rate (s)
Tigv = IGV actuator time constant (s)
Tpf = Ratio of load inertia to system frequency
Tpv = Active power and voltage load model parameter
Tqf = Reactive power and frequency load model parameter
Tpf = Reactive power and voltage load model parameter
Tr = Gas turbine rated exhaust gas temperature (C)
Tref = Reference torque (N m)
xvii
TRH = Steam turbine reheater and conversion time constant (s)
Ts = Droop governor time constant (s)
Tsc = Supplementary control loop torque (N m)
Tt = Temperature controller integration rate (s)
Tv = Valve positioner time constant (s)
Tw = Water time constant (s)
Tx = Gas turbine exhaust gas temperature (C)
Txc = Gas turbine corrected exhaust gas temperature (C)
Txm = Gas turbine measured exhaust gas temperature (C)
TDCR = Combustion reaction time delay (s)
TDTE = Exhaust gas transport delay (s)
u = wind speed (m/s)
V ,v = Voltage (V)
Wf = Gas turbine fuel flow (per unit)
Wx = Gas turbine exhaust gas flow (per unit)
= Blade pitch angle (rad)
Pint,j = Inertial response of generating unit j (MW)
= Tip-speed ratio
= Flux linkage (Wb)
o = Average slip of an average induction machine
= Supplementary control loop time constant (s)
i = Inertial control loop time constant (s)
= Density of air (kg/m3)
= system speed (rad/s)
dq = dq reference frame angular velocity (rad/s)
m = Rotor mechanical angular velocity (rad/s)
s = Shaft speed (rad/s)
t = Wind-turbine rotor speed (rads1)
r = Rotor electrical angular velocity (rad/s)
Subscripts
d, q = Direct, Quadrature axis component
I, P = Integral, Proportional
r, s = Rotor, Stator
xviii
Acronyms
AC Alternating Current
ACE Area Control Error
AGC Automatic Generation Control
BPA Bonneville Power Administration
DC Direct Current
CCGT Combined Cycle Gas Turbine
CER Commission for Energy Regulation
CHP Combined Heat and Power
CLP China Light & Power Co.
CO2 Carbon Dioxide
DFIG Doubly Fed Induction Generator
EMS Energy Management System
ESB Electricity Supply Board
ESBNG ESB National Grid
FOC Field Orientated Controller
GT Gas Turbine
HEC Hong Kong Electric Co.
HRSG Heat Recovery Steam Generator
HVDC High Voltage Direct Current
IEC Israel Electric Corporation
IGV Inlet Guide Vane
NIE Northern Ireland Electricity
NOx Oxides of Nitrogen
OCGT Open Cycle Gas Turbine
POR Primary Operating Reserve
ROCOF Rate Of Change Of Frequency
SCADA Supervisory Control and Data Acquisition
SCIG Squirrel Cage Induction Generator
xix
SO System Operator
SONI System Operator of Northern Ireland
ST Steam Turbine
TH Turlough Hill
TNB Tenaga Nasional Berhad
UFLS Under Frequency Load Shedding
WTG Wind Turbine Generator
xx
Chapter 1
Introduction
1.1 Background
The function of a power system is to provide customers with an electricity supply of
acceptable reliability, where reliability signifies the ability to supply adequate electric
service on a nearly continuous basis with few interruptions over an extended period of
time (IEEE/CIGRE, 2004). Therefore, to design and operate a power system within
adequate reliability margins such that overall costs are minimised is a key objective for
all system operators.
Power system security is an indication of the level of robustness of the power system
at any instant in time to a disturbance (Fink and Carlsen, 1978). When operating
in a secure state, a power system can withstand most severe disturbances without
interruption to customer supply. However, if operating in a state with reduced security
margins, a power system will be more susceptible to disturbance, resulting in a higher
likelihood of customer supply disruption. To maintain adequate reliability it is desirable
to maximise the time the power system is operating in a secure state, with frequency
and voltage levels within acceptable standards. In order for a power system to be
secure, the power system must be operating in a stable state. Stability indicates
the ability of the system to return to an equilibrium operating state subsequent to a
disturbance, and is dependent on both the type of disturbance and the initial power
system operating conditions (IEEE/CIGRE, 2004). Although the electricity industry
is undergoing regulatory and organisational changes, the basic concepts and rules for
1
Chapter 1. Introduction 2
reliable, secure and stable system operation remain unchanged.
Ancillary services can be broadly defined as the range of technical services required
by the system operators to maintain both secure and stable operation of the power
system. These include operating reserves for frequency control, voltage control and also
system restoration/black start capability. While the methods by which these services
are procured may vary and evolve with regulatory structure, the necessity of ancillary
services is unquestionable. This is highlighted by a number of recent contingencies
worldwide resulting in severe lapses in the security of power systems including blackouts
in the Eastern US and Canada, Italy and the UK (NERC, 2004; UCTE, 2003; NGC,
2003).
The control of system frequency is a vital aspect of secure and stable power system
operation. A continuous balance between active power generated and active power
consumed by the load and losses is required to maintain frequency constant at nominal
system frequency. Any imbalance in active power will result in a frequency devia-
tion. While precise instantaneous balancing of active power is not viable, frequency
control ensures that the system frequency remains within acceptable frequency limits.
Frequency control can be called upon for a variety of conditions ranging from a grad-
ual change in load levels over time to a sudden loss of generation or step increase in
demand.
A range of power system characteristics including system size, individual generator and
load frequency response characteristics and plant mix on the system influence frequency
control. The size and speed of a frequency deviation depends on the magnitude of the
power imbalance and the power system size. Power system inertia is the resistance
of the individual rotating masses of the generator and load components synchronised
to the system to a change in system speed. The greater the inertia of the system,
the slower the rate of change of frequency in the event of a power imbalance of given
magnitude. Large interconnected power systems have high system inertia, due to the
large number of components synchronised to the system. In addition, the size of in-
dividual components, such as generators, tends to be small in comparison with total
system size. As such, large frequency excursions from nominal are uncommon, and the
rate of change of frequency is relatively slow due to high inertia. Small isolated power
systems, in contrast, have much lower system inertia. Combined with the fact that a
single generator can comprise a sizeable proportion of total generation, large power im-
Chapter 1. Introduction 3
balances relative to the system size are more frequent and frequency changes are faster.
Adequate frequency control on such a system is vital to prevent the excursion of system
frequency beyond limits where interruption to customer supply through load tripping
starts to occur. Therefore, maintaining system frequency at nominal frequency for a
small island power system with limited interconnection can be technically challenging.
Plant mix is continually evolving, for all power systems, large and small. Knowledge
of the impact that evolving plant mix will have on system frequency control is vital
to maintain a secure and stable power system with adequate reliability standards.
Traditionally large coal and oil fuelled thermal plant comprised the majority of the
generation mix on many power systems. However, due to economic and environmental
driving forces, increasing proportions of combined cycle gas turbines and open cycle
gas turbines are now being used to meet increasing demand and to replace older coal
and oil-fired plants as they are retired.
Combined cycle gas turbines (CCGTs) offer higher efficiency, greater flexibility and
lower emissions than many conventional thermal generators, in addition to progressively
shorter installation times and reducing installation costs. As a result, CCGT generating
units comprise an ever increasing proportion of generation capacity for many electricity
systems. The efficiency of combined cycle gas turbines is maximised when operating at
or near maximum or base load, and declines with decreased loading. The behaviour of
CCGT generators in response to frequency excursions differs from that of a conventional
steam turbine, and may have a detrimental effect on the system frequency response
when the CCGT is run at, or near, base load. This effect will be progressively more
apparent as CCGTs operating at or near base load comprise increasing proportions of
the generation.
In conjunction with the shift towards CCGT plant, many power systems worldwide are
also experiencing a rapid increase in wind generation. This trend is driven by a variety
of reasons including environmental concerns, targets for electricity production from
renewable energy resources, the desire for increased fuel diversity, constant advances
in technology and economic factors including declining costs. While the addition of
conventional synchronous generators to a power system will result in an inherent in-
crease in the system inertial response, this is not necessarily the case with wind turbine
generators. Therefore, if rapidly increasing levels of wind generation begin to displace
conventional synchronous generation, erosion of system inertial response may result.
Chapter 1. Introduction 4
This effect will result in increasing rates of change of frequency during power imbal-
ances, and the magnitude of frequency excursions may also rise. These effects will
influence small isolated power systems, in particular, where system inertia levels are
inherently low.
1.2 Frequency Control of an Island Power System
1.2.1 Frequency Control
System frequency provides a instantaneous indication of system operating conditions,
as any imbalance between active power generated and consumed manifests itself as a
deviation from nominal system frequency. The magnitude of the frequency excursion
and the rate of change of frequency are dependent on a number of factors, including
the size of the power imbalance and the characteristics of the power system. While
small variations in system frequency will not result in a reduction is system reliability
or security, large frequency deviations can have a serious impact on power system
components and power quality is degraded. Damage to generators and transformers
can result from overheating due to increases in the volts/hertz ratio during times of
low frequency. In addition, generator damage due to mechanical vibrations can occur if
frequency deviations greater than 5% of nominal frequency occur (Kirby et al., 2002).
As a result, most power system components are equipped with protective relays, which
are triggered if system frequency reaches critical conditions. Therefore, control of
system frequency is vital for the secure, reliable operation of the power system.
The objective of frequency control is to maintain adequate balance between active
power consumed and generated on a power system such that frequency remains within
acceptable limits around nominal frequency. As the demand of a power system is con-
stantly changing, frequency control is continuously called upon to fulfil this objective.
To a large extent, the changing system load is predictable and generators are committed
and dispatched based on the forecast load levels (Machowski et al., 1997). Therefore,
under normal operating conditions, the balancing of energy is achieved by adjusting
generator active power set-points. Signals to generators for such adjustments are ei-
ther issued by the system operator or automatically generated and issued by automatic
generation control (AGC).
Chapter 1. Introduction 5
In the event of an unpredicted increase in system load or an unexpected loss of genera-
tion or transmission line, an imbalance of active power will occur. Every power system
has stored kinetic energy by virtue of the masses of the generator and load compo-
nents rotating in synchronism, which is a function of both the system inertia and the
system frequency. In response to a power imbalance, stored kinetic energy is released
to redress the imbalance, resulting in an inherent reduction in system frequency. In
the event of active power generated exceeding demand, kinetic energy is absorbed and
an increase in system frequency results. However, while frequency control in the event
of high frequency events is essential and many issues discussed here are relevant, low
frequency events are the focus of this thesis.
In order to limit the frequency excursion from nominal system frequency, and to main-
tain a stable and secure system, action in addition to the inherent system inertial
response is required, i.e. frequency control. Frequency control may be broadly cat-
egorised into automatic and manual frequency control. The former responds auto-
matically to either a deviation from nominal system frequency or a rate of change of
frequency in excess of a predefined threshold. Sources of automatic frequency control
are the natural reduction in system load with low frequency, the automatic increase in
generator active power output activated by the speed droop governor, low frequency
or rate of change of frequency triggered responses from pumped storage units and the
automatic shedding of load. Manual frequency control encompasses all instructions
issued by the system operator to generators (and load if applicable, i.e. in the event
of load participation) for changes from the reference set point of the generator (or to
current active power consumption in the case of load).
Additional active power capacity available (i.e. when compared to steady state oper-
ation prior to a frequency event) from generation units or through reduction in load
for the purpose of frequency control is known as operating reserve (ESBNG, 2005b).
Many different definitions for the categorisation of operating reserve exist. In this the-
sis, reserve is categorised into primary, secondary and tertiary operating reserve, as
defined by ESBNG (2005b), and illustrated in Fig. 1.1.
Primary operating reserve (POR) is the additional active power available from genera-
tors and through reduction of active power consumption of the load which is available
between 5 and 15 seconds subsequent to an event on the system. Secondary reserve is
defined to be the additional active power available and sustainable for the time period
Chapter 1. Introduction 6
Figure 1.1: Operating reserve time-scales (SEI, 2004)
from 15 to 90 seconds after the event. Tertiary reserve is the additional active power
available from 90 seconds to 20 minutes subsequent to the event. Finally replacement
reserve is the additional active power available from 20 minutes to 4 hours after the
event.
In the event of a power imbalance, POR automatically responds to arrest the falling
frequency and initiate recovery towards nominal frequency through the reduction of
the power imbalance. The predominant source of POR on the majority of systems is
the automatic droop governor response of generators operating below maximum rated
active power output to a deviation in speed. Other sources of POR from generators
can include an increase in active power when under-frequency relays or rate of change
of frequency (ROCOF) relays are triggered. One example is under-frequency relaying
triggering a rapid increase in active power generation from a pumped storage generating
unit.
System load also contributes to POR. In addition to the natural load reduction due to
low system frequency, system load can also provide static reserve in the form of either
interruptible customers or under-frequency load shedding (UFLS). Static reserve is
defined here as capacity available instantaneously when called upon, with negligible
dynamics.
Some customers (interruptible customers) are contracted to make their load available
for short term interruptions. Specific blocks of load are configured to be tripped by
Chapter 1. Introduction 7
under-frequency relays if frequency falls to a threshold level. UFLS, however, is the
tripping of uncontracted load at distribution system level and is called upon to pre-
vent system collapse only when other sources of POR fail to arrest falling frequency.
Discrete blocks of load are tripped until generation and load are once again in balance
(Machowski et al., 1997), and frequency decline is arrested.
Once the system frequency has been arrested and stabilised by the POR, it is the task of
secondary and tertiary reserve to restore the system frequency to nominal value. This is
achieved through a combination of automatic droop governor response while frequency
remains below nominal and through discrete instructions issued by the system operator
to generators for changes from the reference set point of the generator until power
is once again balanced, and frequency restored to nominal. Replacement reserve is
employed to replace operating reserve, restoring the system to a secure operating state.
Capacity to provide operating reserve is dispatched in conjunction with generation by
the system operator to ensure availability of adequate operating reserves in the event
of a power imbalance. For a secure system, adequate operating reserve is required
so that the power system can withstand most severe frequency disturbances without
interruption to customer supply. The majority of power system worldwide operate with
an N-1 security criterion (Bialek, 2003). This criterion states that the power system
should operate so instability or load shedding do not occur as a result of the most
severe single contingency. From a frequency control perspective, this entails having
sufficient reserve to withstand the loss of the large power infeeds to the system.
1.2.2 Island Power Systems
Worldwide, power systems have a considerable range of characteristics including size,
both geographical and electrical, the extent of interconnection to other power systems
and generation mix. Many formerly isolated power systems with varying characteristics
have become part of larger synchronous power systems through the use of alternating
current (AC) interconnection. AC interconnection between power systems yields multi-
ple advantages, increased system inertia, trading of energy, sharing of spinning reserve
provision (operating reserve available from online generators) and mutual support dur-
ing contingencies to name just a few (Mak and Law, 1991). While direct current (DC)
interconnection allows energy exchange, power systems linked by DC interconnection
Chapter 1. Introduction 8
are not synchronous. Therefore, some advantages of AC interconnection such as in-
creased system inertia and the sharing of spinning reserves do not inherently occur
with DC interconnection. However, although frequency control is not inherent, DC
interconnections may be designed to provide spinning reserve.
In large interconnected power systems, the size of individual components such as gener-
ators tends to be small in comparison with the magnitude of the entire system. Power
imbalances due to the loss of a single component in such systems, when they occur, are
therefore generally small with respect to the total system size. In addition, the rate at
which the frequency changes tends to be low due to high system inertia. The construc-
tion of sizeable, more economically viable generating units is possible with minimal
risk to system security. In addition, the provision of operating reserve is shared over a
great number of generators, and may be shared between different systems within the
larger interconnected power system. Generally, geographical dispersion is a character-
istic of large interconnected power systems, and can contribute to a reduced capacity
requirement, as a result of load diversity. One example of the benefits of geographical
dispersion is the staggered occurrence of peak demand when a power system spans
different time zones.
While large strongly interconnected systems comprise a large proportion of power sys-
tems worldwide, there are nonetheless a sizeable number of small isolated or poorly
interconnected systems, for example Israel, New Zealand, Crete, Cyprus and Ireland.
Small power systems that are either isolated or with only DC interconnection have low
system inertia. A power system with low system inertia is more sensitive to system
disturbances, due to less stored energy available to redress energy imbalances and to
slow the rate of change of frequency. In addition, for such power systems, system com-
ponents such as generators tend to be large in comparison with the total system size.
In particular at times of low load, a single generator can comprise a large proportion
of the total system generation. Therefore, in the event of a loss of generation, there is
a greater likelihood of a large frequency excursion as the power imbalance is large with
respect to total system size. On the Ireland electricity system, for example, frequency
deviations of 1% are not uncommon, while larger frequency excursions occur occasion-
ally, as illustrated by the recorded system frequency in Fig. 1.2. (This frequency event
is described in more detail in Appendix A.)
As a consequence of both low system inertia and potential large power imbalances
Chapter 1. Introduction 9
0 100 200 300 400 500 600 700 80048.4
48.6
48.8
49
49.2
49.4
49.6
49.8
50
Time (s)
Freq
uenc
y (H
z)
Figure 1.2: Recorded system frequency on Ireland electricity system
in addition to the relatively small range of generators to provide operating reserve,
frequency control on small, isolated or DC interconnected systems is particularly chal-
lenging. Distinctive operating and control strategies are necessary to maintain the
system within limits of reliability and security. The main dynamic operation problems
in small power systems relate to frequency control, in particular the behaviour of the
system in response to large disturbances (Kottick and Or, 1996). Frequency control
on such systems can in fact cause technical problems an order of magnitude greater
than those experienced on large interconnected systems (OSullivan et al., 1999). The
importance of frequency control on island systems during a contingency is evident in
the considerable volume of relevant literature.
1.2.3 Literature Review
The benefits of AC interconnection between power systems are highlighted in Mak and
Law (1991), where the AC interconnection between The China Light & Power Co.
Chapter 1. Introduction 10
(CLP) and Hong Kong Electric Co. (HEC) are examined. The evolution of CLP from
an isolated system to one with AC interconnection to other systems was found to have
beneficial effects on system performance during system contingencies and also resulted
in a more economical system operation. However, AC interconnection is not always an
option and therefore a clear understanding of the frequency control dynamics of island
power system is necessary to ensure optimal system security and reliability.
Two neural network models that predict the frequency nadir (minimum frequency)
and calculate the amount of UFLS during a loss of generation on the Israel Electric
Corporation (IEC) system are developed in Kottick and Or (1996). The IEC operates
an island system and at the time of the study the installed capacity was approximately
5050 MW, with a 550 MW unit as the largest infeed. As the transmission system is
strongly connected, frequency throughout the system is uniform. Therefore, transmis-
sion effects could be neglected and a single busbar model was employed. Both the
magnitude of the frequency excursion and the extent of UFLS are indicators of the
severity of the contingency, and comprise two components of the dynamic security as-
sessment for the IEC system. The models developed were demonstrated to perform
well in assessing the UFLS subsequent to a loss of generation. The potential effect on
frequency regulation (which is the automatic power balancing on a second to second
basis) of a 25 MWh capacity battery energy storage device on the IEC system was
investigated in Kottick et al. (1993), where a single busbar model was again used to
represent the power system. It was demonstrated that simulated frequency deviations
resulting from sudden demand variations were reduced considerably through the ad-
dition of the battery energy storage device, which was assumed capable of sustaining
a power output of 30 MW for 15 minutes. Due to a fast response time, the battery
energy storage device was found to be potentially useful for regulation and as rapid
operating reserve on an island system, where the rapid response time is critical due to
low system inertia.
The application of UFLS to the isolated power system of Cyprus is considered in Con-
cordia et al. (1995). At the time of the study, the Cyprus system (with a peak load of
500 MW) had a largest infeed of 60 MW, which was 12% of peak load and comprised
a significantly greater proportion of load at times of low demand. While the general
principles of UFLS are independent of system size, the distinguishing characteristics
of isolated system must be taken into account when devising the UFLS plan. A well
devised UFLS schedule results in the system surviving situations that would have oth-
Chapter 1. Introduction 11
erwise resulted in blackouts. In Concordia et al. (1995), a criteria deemed appropriate
for UFLS on an isolated system was developed and applied to the Cyprus system. It
was also found that the effectiveness of load shedding increases with increasing system
load.
The effects of increasing proportions of renewable generation resources on the system
frequency control on the island of Crete have been the focus of several studies (Hatziar-
gyriou et al., 2000, 2002; Papazoglou and Gigandidou, 2003). In particular, Crete has
experienced a rapid growth in wind generation in recent years. These studies pre-
dominantly focus on the system under non-contingency operating conditions over the
economic dispatch and unit commitment time frames. The short-term dynamic effects
of wind turbine generators on the system frequency during a frequency event are not,
however, considered.
Another example of an island electricity system is the Ireland power system, which con-
sists of two synchronous power systems. Before interconnection between the Northern
Ireland Electricity (NIE) system and the Electricity Supply Board (ESB) system of the
Republic of Ireland, each system on the island of Ireland operated as a small isolated
system. With peak loads of approximately 1650 MW and 3300 MW respectively before
interconnection, each system had low system inertia and as a result emergency control,
i.e. frequency control in the event of a contingency, was critical.
The strategies of the NIE system for emergency control of frequency when operating
as an isolated system are outlined in Fox and McCartney (1988). Several obstacles
such as inaccurate unit response information and difficulties with the coordination of
under-frequency relay settings with system dynamics are also discussed. Limited UFLS
was tolerated as a likely necessity on the NIE system at the time of the study in the
event of the loss of a major infeed. Further studies into the control and proper design
of UFLS arrangements are carried out in Fox et al. (1989) and Thompson and Fox
(1994). The use of rate of change of frequency as an activating signal for UFLS was
used in Fox et al. (1989), and found to provide more accurate load shedding than
the use of under frequency relays. System frequency was simulated using a single
busbar model. This approach was expanded in Thompson and Fox (1994), where each
UFLS relay uses system demand, spinning reserve, system inertia and the amount of
low priority load available for shedding elsewhere in conjunction with the local rate of
change of frequency to assess whether to operate. This approach resulted in a significant
Chapter 1. Introduction 12
reduction in the amount of excessive UFLS when compared to the fixed rate of change
of frequency scheme of Fox et al. (1989). The effect of flywheel energy injection on
emergency control of frequency on the NIE system has also been studied (Hampton
et al., 1991). Once again a single busbar system model to predict system frequency
following a unscheduled generation outage was used, and the model was validated by
comparison to actual power system measurements. It was found that the use of the
flywheel energy storage and retrieval scheme can contribute to considerable savings
through spinning reserve replacement if correctly designed and scheduled.
An emergency reserve model of the ESB system was developed and implemented to
study frequency control on an island power system in OSullivan and OMalley (1996),
OSullivan (1996) and OSullivan et al. (1999). The single busbar model was tuned
using actual frequency events on the ESB system to accurately account for the dy-
namic system characteristics following a loss of generation. The provision of frequency
control was shown to be a critical issue as electricity markets emerge for island systems
(OSullivan et al., 1999). As a result, the above model was subsequently incorporated
into a new methodology for the provision of reserve in a competitive market (OSullivan
and OMalley, 1999).
1.3 The Aims and the Scope of this Thesis
The objective of this thesis is to examine frequency control on an island system with
evolving plant mix. In particular, the influence of the characteristics of CCGTs and
wind turbine generators on system frequency control will be examined, and the Ireland
electricity system is used as an illustration.
Simulation, using validated models, is a good first step in understanding frequency
control in the context of evolving plant mix. A single busbar model of the Ireland
electricity system is developed, tuned and validated in Chapter 2. This model is suitable
for the study of frequency response behaviour of an island system for up to 20 seconds
after a power imbalance occurs. This system model is subsequently employed to tune a
black-box model, which is used as the basis for the derivation of a minimum frequency
control constraint (Appendix C).
A model suitable for studying the short-term dynamic response of a combined cycle gas
Chapter 1. Introduction 13
turbine to a system frequency deviation is developed, tuned and validated in Chapter
3. This model is then used in conjunction with the Ireland system model of Chapter 2
to study the impact of increasing levels of CCGT generation on frequency control of a
small island system (Appendix B).
Models for two different wind turbine technologies are presented in Chapter 4. To
examine the short-term dynamic response of an island power system to sudden power
imbalances with increasing proportions of wind generation, these models are integrated
into the Ireland system model of Chapter 2, which is modified to represent the proposed
2010 system model (Appendix D).
The impact of wind generation on both short-term and long-term frequency control
are assessed in Chapter 5. A review of a number of wind integration studies is carried
out. Consequently, a preliminary methodology for a wind integration frequency control
study using the Areva T&D e-terra simulator is proposed, which is applicable to both
island and interconnected power systems. This work was carried out during a three
month industry placement with Areva T&D in Bellevue, Washington.
Chapter 2
System Model
2.1 The Ireland Power System
The electricity system on the island of Ireland operates at 50 Hz, with a current peak
load of approximately 6100 MW (ESBNG, 2004b; SONI, 2003b). The Ireland electricity
system consists of two power systems: the NIE system, operated by System Operator
for Northern Ireland (SONI) and the ESB system, operated by ESB National Grid
(ESBNG). Prior to 1995, the ESB and NIE power systems operated in isolation, with
the limited connection between the two systems generally out of service and, as a
consequence, unreliable (OSullivan, 1996). In 1995, however, the two systems were
reconnected, and now comprise a single synchronous system, connected to each other
through a number of AC lines. The main connection between the NIE and ESB systems
consists of two 275 kV circuits, each with a capacity of 600 MW and of length 50 km.
There are also two additional 110 kV lines, with capacity of 120 MW, connecting
the systems at two separate locations along the interface between Northern Ireland
and the Republic of Ireland (ESBNG, 2004a). A single high voltage direct current
(HVDC) interconnection is in operation between Northern Ireland and Scotland with
a capacity of 500 MW (ESBNG, 2004b). However, this HVDC interconnection is not
currently configured to provide frequency response in the short time frame. With no
AC interconnection to other systems to increase the inertia of the system and share
reserve provision requirements, the Ireland electricity system is essentially an isolated
system.
Chapter 2. System Model 15
The generating capacity of the Ireland electricity system consists of a combination of
reheat and non reheat fossil fuelled steam turbine generators, open cycle gas turbines
(OCGTs), combined cycle gas turbines (CCGTs), hydroelectric generators, a single
pumped storage station and wind turbine generators. In addition, other resources such
as biomass generators, combined heat and power (CHP) and other renewables also
provide limited generating capacity. Generation mix is constantly evolving, with both
CCGTs and wind turbine generators in particular comprising increasing proportions of
generation on the system. A comparison of the generation mix on the Ireland system
in 2005 with the ESB and NIE systems in 1995 is illustrated in Fig. 2.1.
Figure 2.1: Generation mix on the Ireland electricity system for 1995, 2005 and 2010((SONI, 2003b; ESBNG, 2004b))
The reduction in the proportion of steam units from 1995 to 2005, alongside the increase
in proportions of both CCGT and wind generation is clearly illustrated. The predicted
Ireland generation mix in 2010 is also included in Fig. 2.1, to illustrate the forecast
changing proportions of generation on the system.
The system operator (SO) of each system performs scheduling and dispatch indepen-
dently, while incorporating contracted flows on the interconnections between the two
systems. The provision of primary operating reserve, however, is shared between the
two systems.
Chapter 2. System Model 16
In accordance with the system grid codes (ESBNG, 2005b; SONI, 2003a) frequency
regulation is provided by each generator on the system, by virtue of a droop governor,
with a compulsory droop setting of 4%. Operating reserve is divided into several
categories according to the timescale within which it is available in response to an event,
as described in Chapter 1. On the Ireland system, the primary operating reserve (POR)
requirement corresponds to 75% of the largest infeed onto the system. At present, the
largest infeed is 422 MW (the 500 MW HVDC interconnection to Scotland is operated
with a maximum limit of 400 MW for system security reasons i.e. to limit the size
of the largest infeed), thus making the primary reserve requirement 317 MW. The
availability of primary reserve to meet this requirement is divided such that the ESB
and NIE systems provide 67% (211 MW) and 33% (105 MW) respectively. Sources of
POR include spinning reserve from generating units online and static reserve, such as
interruptible load. Static reserve consists of blocks of reserve that are available almost
instantaneously when tripped by the system frequency falling below the predetermined
frequency setting of each block. Interruptible load is a form of static reserve, whereby
certain load on the power system has an agreement with the SO that some or all of
the load may be tripped during certain hours when the frequency falls below 49.3 Hz.
The proportion of the POR provided by spinning and static reserve sources varies with
time of day. The contribution of the pumped storage station to POR depends on the
operational mode in which it is running, as described later in Section 2.2.2.
2.2 Modelling the Ireland Power System.
The dynamic model of the Ireland system used in this thesis is based on two previous
models (OSullivan, 1996; Fox et al., 1989), with considerable enhancements introduced.
An emergency reserve model of the ESB electricity system circa 1995 was developed
by OSullivan (1996). The objective of this single busbar model was to accurately
predict the system frequency following a contingency, by simulating the primary reserve
response of the system. Installed generators are represented using low order models,
and include dynamics for prime mover, turbine and governor valve characteristics where
appropriate. A low order model, derived based on consideration of resistive and motor
loads, is used to represent the system load. A similar single busbar model of the isolated
NIE system circa 1989 was applied in Fox et al. (1989) for the evaluation of emergency
load shedding schemes.
Chapter 2. System Model 17
The present Ireland electricity system has evolved and developed from the ESB and NIE
systems represented in OSullivan (1996) and Fox et al. (1989) respectively. A sizeable
growth in system load has occured and new generating plants have been introduced onto
the system and older plants decommissioned and removed. In particular, proportions
of both combined cycle gas turbines and wind generation have increased significantly,
and are predicted to comprise increasingly large proportions of system generation mix
in the future, as illustrated in Fig. 2.1.
The dynamic model representative of the Ireland electricity system is developed based
on OSullivan (1996), and also Fox et al. (1989), augmented with more detailed and
additional models where necessary. Each generating unit on the Ireland system is
individually modelled, with the exception of wind, small hydro and other generators
subject to a de minimis level of 10 MW. The details of the individual unit models are
given in Section 2.2.2. The load model is presented in Section 2.2.3, and an overview
of the entire Ireland model, with details of the connecting system and is presented in
Section 2.2.4. The development and tuning of the Ireland electricity system model
was carried out in collaboration with Dr. Damian and Flynn and Julia Ritchie of the
Queens University of Belfast.
2.2.1 Assumptions of the Model
A fundamental assumption made in the development of the system model is that fre-
quency is uniform throughout the system. This assumption is made on the basis that
the electricity system of Ireland is tightly meshed and electrically short, with the rel-
ative impedances between nodes quite small. Therefore, during a major contingency
involving the loss of significant generation, the system will remain in synchronism and
the frequency deviation will be very similar at all points on the system. This is borne
out by system studies carried out by the Transmission System Operators and by fre-
quency measurements during major events with frequency deviations of up to 0.8 Hz
during sudden generation deficits. The system is designed and operated so that in
the event of the loss of the largest infeed there should be no consequential events (i.e.
the protection does not trip out any other devices, for example lines). Historical data
shows that the loss of a transmission line has never occurred during a loss of generation
event. In particular, during a major loss of generation there are noticeable changes in
power flow across the AC lines between the NIE and ESB systems, due to the shar-
Chapter 2. System Model 18
ing of reserve (DETINI, 2003; ESBNG, 2005c). These rapidly changing power flows
have never caused any additional tripping of lines. Therefore, for frequency control
studies on the Ireland electricity system, a uniform system frequency is assumed and
a single busbar model has traditionally been employed (OSullivan, 1996; OSullivan
and OMalley, 1996; OSullivan et al., 1999) and is appropriate for this study. It is
also assumed that changes in voltage have negligible effect on real power balance on
the system. In the event of a loss of generation on the system, voltage deviations will
occur around the site of the contingency. However, these effects are only local and will
not manifest themselves globally (OSullivan, 1996).
The objective of the development of the Ireland electricity system model is to examine
the effect of evolving plant mix on frequency control during a frequency event. The
timescale of interest is the time immediately prior to and the first 20 seconds of a
frequency disturbance event. For the purpose of short-term frequency control, as of
interest in the system model, dynamics outside the timescale of interest are neglected.
In addition, the system is assumed to be in steady state at nominal frequency prior to
any frequency event.
On the Ireland electricity system, if the frequency falls below 49.7 Hz (99.4% of nom-
inal), it is deemed to be a significant frequency disturbance event (ESBNG, 2005b).
Below 47.5 Hz (95% of nominal), the system will lose synchronism as generating units
and load trip off the system. The system model is designed for relatively small fre-
quency deviations of less than 3% ( 1.5 Hz). Therefore, system frequency changes
can be assumed to be small with respect to nominal system frequency.
2.2.2 Generation
The majority of electricity generating units consist of a prime mover to produce me-
chanical energy and a generator to convert this mechanical energy into electrical energy
suitable for supply to the power system (Machowski et al., 1997). A variety of energy
resources may be used to impart energy to the prime mover, resulting in a number
of different prime movers types. These can be broadly categorised as steam turbines,
combustion turbines and turbines which are driven directly by the energy resource,
such as hydroelectric turbines, wind turbines and tidal energy turbines.
Chapter 2. System Model 19
The energy resources associated with steam units are generally fossil fuels and nu-
clear fission. The energy from combustion of the fuel (or heat energy resulting from
the nuclear fission) is used to produce steam in a boiler, which drives the steam tur-
bine. Combustion turbines, alternatively, use the exhaust gases from the combustion
reaction to drive the prime mover. Hydroelectric turbines can have many different con-
figurations, but water is used to drive the prime mover in all cases. Similarly, energy
from wind and tides can be extracted in appropriately designed turbines to produce
mechanical energy to convert into electrical energy in the generator.
Steam Units
Fossil fuelled steam units have been in use for over 120 years and can have a number of
different configurations. However, the basic principle remains the same: the combustion
of the fuel in the furnace heats the water in the boiler to produce steam, which is used
to drive the steam turbine. Thus, the working fluid for a steam unit is water. The
rotational energy of the steam turbine is then converted to electrical energy in the
synchronous generator.
The boiler can be either drum or once through configuration. In a drum boiler, water
enters the waterwalls from the reservoir of water in the drum. Heat energy from the
fuel combustion process is transferred through conduction, convection and radiation to
the water in the waterwalls. The resultant steam and water mixture then re-enters the
drum. In the drum, steam separates from water and travels to the steam turbine, via
the superheater, with steam flowrate dependent on the pressure differential between
drum and turbine. The pressure in the drum is dependent on the fuel firing rate, and
steam flowrate can therefore be controlled by adjusting the firing rate. Superheated
steam temperature is controlled by means of spray water attemperation (Flynn, 2003).
Drum boilers may use either natural or forced circulation, but natural circulation is
the more common configuration. Although higher pressure, and thus efficiency, can be
achieved through the use of pumps, it is generally only viable in very large plants.
The once through boiler configuration contains no internal reservoir and the water is
forced through a continuous pipe to the steam turbine by means of pumping. As a
result, steam flowrate is determined by the boiler feed pump and steam temperature
is controlled by adjusting the fuel firing rate. Once through boilers are designed to
Chapter 2. System Model 20
operate at supercritical temperatures, yielding higher efficiency. However, although
increased efficiency results in reduced operating costs, the increased installation costs
of such boilers generally make drum boilers more economically viable (Flynn, 2003).
Boiler dynamics are highly complex, and over long time frames, detailed models are
required to accurately capture dynamic behaviour. Complex models derived from phys-
ical principles have been developed (Chien et al., 1958; McDonald and Kwatny, 1970;
Kwan and Anderson, 1970; Flynn and OMalley, 1999) to capture the dynamics of the
boiler over different timescales. A low order nonlinear boiler model was developed in
IEEE (1973b). In this model, pressure and steam flowrate are defined as functions of
the energy input to the boiler and the turbine control valve area.
DeMello (1991) examined and justified the use of simplified boiler models (IEEE,
1973b) for power system modelling. Various simplified models, which captured the
essential nonlinear characteristics of the boiler, were compared to a detailed model
based on mass, volume and energy balance equations and found to be adequate for use
in power system dynamic performance studies. The simplified model of IEEE (1973b)
and DeMello (1991) was adopted for the emergency reserve model of OSullivan (1996),
and is employed in the Ireland system model of this thesis to model the boiler compo-
nent of the steam units on the Ireland system.
The boiler model is illustrated in the schematic of the steam turbine model in Fig. 2.2,
which also includes the steam turbine model and the governor model.
There are time delays in a boiler associated with the fuel dynamics and the transfer of
heat energy to the water in the waterwalls when generating steam. The time constant
for the fuel dynamics varies from 20 to 40 seconds depending on the fuel type in use.
The waterwall lag has a time constant of approximately 5 seconds. Due to the relatively
long time constant for the fuel dynamics in comparison with the time scale of interest
here, the heat energy, Q, can therefore be assumed constant. However, as the heat
energy Q remains constant, the waterwall lag component, a first order lag, may be
neglected. Therefore, steam generation mw is equal to the heat energy Q.
Pressure in the drum, PD, is proportional to the integral of the difference between the
steam generation mw (i.e. steam flowing into the drum) and the steam flowrate out of
the drum, m. The throttle pressure at the entrance to the steam turbine valve, PT , is
propotional to the integral of the difference between the steam flowrate from the drum,
Chapter 2. System Model 21
Figure 2.2: Steam unit model (See text for details)
m and the steam flowrate exiting the valve into the steam turbine, ms. The non-linear
nature of the boiler process is due to the steam flowrate from the drum to the throttle,
which is proportional to the square root of the pressure difference between the two.
From the boiler, the steam enters the steam turbine, where the heat energy in the steam
is converted to rotational energy to turn the turbine. When a gas passes through
a nozzle, it expands converting heat energy into mechanical energy. Therefore, as
the steam expands through the stages of the steam turbine blades, temperature and
pressure drop as the energy is imparted to the rotating turbine.
A model which can represent both reheat and non-reheat turbine systems is presented
in IEEE (1973a). This model, also used in IEEE (1991) and OSullivan (1996), is
employed to model the steam turbine component of the steam units in this thesis, as
illustrated in Fig. 2.2.
The steam flow entering from the boiler, ms, directly determines the power generated
in the turbine, with appropriate time delays incorporated. In a reheat steam turbine,
three time delays are required. The time delay for transport of steam from the boiler
to the first turbine stage and also the conversion of steam to rotational energy in the
first or high pressure turbine stage is represented using a first order lag with a time
Chapter 2. System Model 22
constant TCH . The time delay due to the reheater and conversion of heat energy to
rotational energy in the intermediate stage is captured by the first order lag with time
constant TRH . Finally, the transport delay to the final or low pressure turbine stage as
well as the conversion of heat to rotational energy in this stage is captured by the a first
order lag with time constant TCO. The fractions of the total power output generated
at each stage are represented by FHP , FIP and FLP . A non-reheat unit will result in
all power generation coming from the high pressure stage and therefore FIP and FLP ,
the fractions of the total power generated in intermediate and low pressure stages of
the steam turbine, will be zero.
All dispatchable generating units on the Ireland system are fitted with droop governors
and required by regulations (ESBNG, 2005b; SONI, 2003a) to have a droop setting of
4%. The governor model used for the steam turbine units is the simplified speed
governor of Elgerd (1982), and is illustrated in Fig. 2.2. Using the difference between
actual and nominal frequency as input, the signal to the control valve is determined,
which is proportional to the inverse of the droop, Rd. A time delay with time constant
Ts due to the action of the hydraulics associated with the turbine valves is incorporated,
along with maximum and minimum limits (Pmax and Pmin) to maintain the valve area
within actual limits.
Open Cycle Gas Turbine Units
In the open cycle gas turbine, the working fluid is air. Air at atmospheric conditions
enters the compressor, where energy is imparted to the air from the spinning compressor
stages. On exiting the compressor, the air enters the combustion chamber where fuel is
added and combustion occurs, resulting in the conversion of chemical energy in the fuel
into heat energy. The hot gases produced by the combustion process then enter the
gas turbine under high pressure and are expanded as they pass through the different
turbine stages, converting the heat energy of the gases into rotational energy of the
gas turbine. The gas turbine, compressor and generator rotate on a single shaft. The
mechanical energy produced by the turbine, less the mechanical energy required by the
compressor, is the net mechanical energy and this is converted to electrical energy in
the synchronous generator.
Numerous models of gas turbines have been developed, with varying degrees of com-
Chapter 2. System Model 23
plexity and detail (Rowen, 1983b; Hung, 1991; Cohen et al., 1996; Kunitomi et al.,
2001; Pourbeik, 2002). The dynamic model developed by Rowen (1983b) incorporates
the main dynamics of a gas turbine for a wide range of operating speeds (95 - 107%)
and conditions, and is suitable for use in power system stability studies. As a result,
this model is used as the basis for many gas turbine and combined cycle gas turbine
modelling applications (Bagnasco et al., 1998; Kunitomi et al., 2001; Lalor et al., 2005).
The model developed in Rowen (1983b) includes the relationships between pertinent
gas turbine components and also the control systems for speed, temperature and ac-
celeration in addition to maximum and minimum fuel limits. Further simplifications
of the model are also outlined.
At the time of development of the emergency reserve model (OSullivan, 1996), a num-
ber of OCGTs existed on the ESB system. However, due to an absence of data for any
gas turbines during frequency events, identification of the dynamic parameters for the
gas turbine model of Rowen (1983b) was not possible (OSullivan, 1996). As a result,
a simple ramp based model was implemented, using the approximate reserve charac-
teristics supplied by the system operator to provide limited identification (OSullivan,
1996).
For the Ireland system model developed here, OCGT generating units are explicitly
modelled, using a model adapted from that of Rowen (1983b). The OCGT model
structure is illustrated in Fig. 2.3.
As acceleration control generally only comes into play during start-up and shut-down,
the acceleration controller is neglected in this model, due to the assumption that the
model is initially generating in steady state. The output from the speed and temper-
ature controllers feeds into a minimum selector, where the lower of the two signals
determines the fuel flow. Under normal operating conditions, the fuel flow is under
the control of the speed controller (the governor). The speed controller consists of a
simple droop governor. The temperature control loop compares the measured temper-
ature of the exhaust gases, Txm, to the rated exhaust temperature, Tr. If measured
exhaust temperature exceeds rated exhaust temperature, the temperature controller
signal falls below unity, and the temperature controller takes over the fuel flow control.
The exhaust temperature Tx is calculated using the equation (2.1):
Chapter 2. System Model 24
Figure 2.3: Open cycle gas turbine model (See text for details)
Tx = Tr 700 (1Wf) + 550 (1N) (2.1)
where Wf is the gas turbine fuel flow (per unit) and N is the system speed (per unit).
Power output is the product of the torque and the system speed, where the torque
produced by the gas turbine is determined by the equation (2.2):
Torque = 1.3 (Wf 0.23) + 0.5 (1N
Nref) (2.2)
where Nref is the reference system speed (per unit).
Combined Cycle Gas Turbine Units
Combined cycle gas turbines fuse the technologies of both steam and gas turbine units,
resulting in a unit capable higher efficiency than either of the two individual compo-
nents. CCGTs are not included in the emergency reserve model of OSullivan (1996).
Chapter 2. System Model 25
However, due to a significant increase in CCGT generation on the ESB system, these
units comprise a large proportion of total generating capacity. The details of the
CCGT model structure used for the system model in this thesis, together with the
CCGT model tuning and validation methodology are given in Chapter 3, where the
impact of CCGT short term dynamics on frequency control is studied.
Hydroelectric Units
Hydroelectric generation uses the potential energy contained in water moving from a
higher to a lower height to turn a turbine. Thus the potential energy is converted into
kinetic or rotational energy of the turbine, which in turn is connected to an electric
generator where kinetic energy is converted to electrical energy. There are three prin-
cipal forms of hydro-turbines available and choice of turbine will depend on both the
potential energy or head of the water supply and also the volume of water available.
The three types are the Francis turbine, the Kaplin turbine and the Pelton wheel (Kun-
dur, 1994). Both Francis and Kaplin hydraulic turbines are reaction turbines, relying
on the weight of the water column to react against blades of the rotating element of
the turbine, the runner. The runner is fully immersed in water and is enclosed in a
pressure casing. The pressure differences across the runner blades imposes lift forces,
which cause the runner to rotate. Francis turbines are the most widely used turbine
type and designed to operate under medium heads of water, while the Kaplan turbine
generally operates under lower heads of water with higher flow rates. Pelton wheels are
impulse type turbines where the runner is spinning in air and rotated by the impact of
a water jet on the blades. These are generally used only with high heads of water.
One distinctive property characteristic of hydroelectric generation is the initial drop in
power output that occurs when the opening of the intake gate is increased. This non-
minimum phase characteristic is caused by the inertia of the water and the momentary
reduction in head that occurs when the gate initially opens further, before the water
flow through the turbine increases again (Elgerd, 1982; OSullivan, 1996). Therefore
adequate representation of this phenomenon is required for accurate dynamic models
of hydroelectric generating units, in particular for frequency control.
The two hydro-turbine types used for generation on the Ireland system are Francis and
Kaplan hydraulic turbines (OSullivan, 1996; ESBNG, 2004). A number of different
Chapter 2. System Model 26
models for hydraulic hydro-turbines and their speed controllers
Top Related