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Operation of Market-oriented Power Systems 2003 ed. [Hardback]

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  • Formāts: Hardback, 443 pages, height x width: 223x152 mm, weight: 1430 g, XVIII, 443 p., 1 Hardback
  • Sērija : Power Systems
  • Izdošanas datums: 01-Sep-2003
  • Izdevniecība: Springer London Ltd
  • ISBN-10: 1852336706
  • ISBN-13: 9781852336707
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Operation of Market-oriented Power Systems 2003 ed.Palielināt
  • Formāts: Hardback, 443 pages, height x width: 223x152 mm, weight: 1430 g, XVIII, 443 p., 1 Hardback
  • Sērija : Power Systems
  • Izdošanas datums: 01-Sep-2003
  • Izdevniecība: Springer London Ltd
  • ISBN-10: 1852336706
  • ISBN-13: 9781852336707
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9781852336707.html
Keywords:
Internationally, the electric power industry is currently undergoing unprecedented reform.  Power utilities need efficient tools to ensure that electrical energy of the quality desired can be provided at the lowest possible cost. Operation of Market-oriented Power Systems provides effective computational tools for the efficient operation of restructured power systems covering all the major operational issues such as:



congestion management;



available transfer capability calculations;



price forecasting and optimal bidding strategies;



a review of international research and world-wide industrial practice covered in each chapter gives the reader a broader understanding of the state of the art in this exciting field.



This book will be a useful reference for professional engineers and researchers in the operation and control of modern power systems as all within the power industry face up to the changes required to provide safe, reliable and profitable electricity in an increasingly competitive market.
List of Contributors
xvii
Operation of Restructured Power Systems
1(12)
Y.H. Song
X. Wang
J.Z. Liu
System Operation in a Competitive Environment
1(2)
Reliability-related Functions
2(1)
Market-related Functions
2(1)
Effects of Industry Restructuring on System Reliability
3(2)
New Requirement for Computation Tools and Software Systems in Electricity Markets
5(2)
Outline of the Book
7(5)
References
12(1)
Modelling and Analysis of Electricity Markets
13(38)
A. Maiorano
Y.H. Song
M. Trovato
Types of Markets
14(2)
Fundamental Market Structure and Mechanism
15(1)
Commodity Markets
16(2)
Cash Market
17(1)
Futures Market
17(1)
Options Market
17(1)
Swap Market
17(1)
Planning Market
17(1)
Perfect Competition and Oligopolistic Market
18(13)
Market Equilibrium: The Law of Supply and Demand
19(2)
Elasticities of Supply and Demand
21(1)
Perfect Competition
22(2)
Classical Theories of Oligopoly
24(1)
The Cournot Model
24(1)
Isoprofit Curves and Reaction Functions
25(3)
The Bertrand Model
28(2)
The Stackelberg Equilibrium
30(1)
Oligopolistic Electricity Market
31(9)
Modelling of the Load Demand
32(2)
Evaluation of Company Marginal Cost Functions
34(1)
Presence of Transmission Losses
35(2)
Proposed Model
37(2)
Presence of Bilateral Contracts
39(1)
Case Studies and Results Analysis
40(6)
Conclusions
46(2)
References
48(3)
Location-based Marginal Pricing of Electricity and its Decomposition
51(32)
K. Xie
Y.H. Song
Introduction
51(1)
Spot Pricing Models
52(4)
Review of Some Existing Spot Pricing Models
52(1)
The Decomposition Model
53(3)
Lagrangian Multipliers, Marginal Cost and Spot Price
56(2)
Integrated Sensitivity Calculation
58(3)
Loss Sensitivity
58(1)
Sensitivity Coefficients of an AC Network Model
59(2)
Decomposition Model of Spot Pricing
61(7)
Framework
61(2)
Optimal Spot Pricing
63(2)
Spot Price Decomposition
65(1)
Implementation
66(2)
Features of the Proposed IOSP Model
68(2)
Comparison with Existing Models
68(1)
The Inner Connection with Economic Dispatching (ED)
69(1)
Numerical Studies
70(8)
Case Study 1: Insight View of a 5-bus System
70(5)
Case Study 2: IEEE 30-bus System
75(1)
Case Study 3: 118-bus System
76(2)
Summary
78(1)
List of Principal Symbols
79(1)
References
80(3)
Coordinated Real-time Dispatch of Unbundled Electricity Markets
83(30)
X. Wang
Y.H. Song
M. Tan
Power System Operation
84(2)
Operation in Vertically Integrated Utilities
84(1)
Operation in Competitive Electricity Markets
85(1)
Coordinated Real-time Dispatch through Balancing Mechanism
86(5)
Bilateral Contract Market
88(1)
Pool Day-ahead Energy Auction Market
88(1)
Pool Ancillary Services Auction Market
88(1)
Real-time Balancing Market and Coordinated Dispatch
89(2)
Mathematical Model of the Proposed Framework
91(7)
P Sub-problem
91(1)
Objective
91(1)
Equality Constraints
92(1)
Inequality Constraints
93(1)
Pricing for Real-time Active Power Dispatch
93(2)
Meeting Real-time Imbalance of Market under Normal Operating Condition
95(1)
Replacement of Operating Reserves
96(1)
Curtailment of Bilateral Contracts
97(1)
Q Sub-problem
97(1)
Imbalance Settlement Methodologies
98(1)
Implementation
99(1)
Test Results
100(5)
Coordinated Dispatch without Network Congestion
101(1)
Coordinated Dispatch with Network Congestion
102(2)
Comparison Between the RSLP and PDIPLP
104(1)
Conclusions
105(1)
References
105(8)
Appendix A: Primal-dual Interior Point Linear Programming Method
106(7)
Available Transfer Capability Evaluation
113(34)
Y. Xiao
Y.H. Song
Y.Z. Sun
Definition and Application of ATC
113(3)
Definition of ATC
113(2)
Industrial Applications of ATC
115(1)
Criteria for ATC Evaluation
116(2)
Accuracy
117(1)
Dependability
117(1)
High Efficiency
118(1)
Review of Existing Methodologies for ATC Evaluation
118(3)
Existing Methodologies
118(1)
Sensitivity Analysis
118(1)
Continuation Power Flow
118(1)
Optimal Power Flow
119(1)
ATC Evaluation in Industry
119(1)
EPRI [ 19]
120(1)
ECAR [ 20]
120(1)
PJM [ 7]
120(1)
NYISO [ 21]
121(1)
Proposed Stochastic Model for ATC Evaluation
121(3)
Overview of Proposed Approach
121(2)
Modelling Uncertainties
123(1)
Formulated ATC Evaluation Model
124(2)
Objective Function
124(1)
Operating Constraints
124(2)
Proposed Hybrid Stochastic Approach
126(7)
Application of SPR to Deal with Discrete Variables
127(1)
Application of CCP to Deal with Continuous Variables
128(5)
Implementation
133(1)
Case Studies and Interpretation of Results
133(6)
Conclusions
139(1)
References
140(7)
Appendix A: Stochastic Programming with Recourse (SPR)
142(2)
Appendix B: Chance-constrained Programming
144(2)
Appendix C: Line Thermal Limits of IEEE 118-bus System
146(1)
Transmission Congestion Management
147(30)
X. Wang
Y.H. Song
Q. Lu
General Methodologies for Congestion Management
148(4)
Transaction Curtailment
148(1)
Transmission Capacity Reservation
149(1)
System Redispatch
150(1)
Overall Congestion Management Process
151(1)
International Comparison of Congestion Management Approaches
152(6)
UK Market
152(1)
Congestion Management in Previous Energy-trading Arrangement
152(1)
Congestion Management in NETA
153(1)
PJM Market in the US
154(1)
California Market in the US [ 3, 15]
155(2)
Norway and Sweden Market [ 8--15]
157(1)
New Zealand Market [ 15--17]
158(1)
Real-time Congestion Management across Interconnected Regions
158(14)
Proposed Method for Regional Decomposition OPF
159(4)
Application of the Proposed Method to Congestion Management across Interconnected Regions
163(1)
Mathematical Model
164(1)
Sequential Solution versus Parallel Solution
165(1)
Global Congestion Management versus Two-level Congestion Management
165(1)
Test Results
166(1)
Case 1: Inter-regional Congestion Management
166(3)
Case 2: Intra-regional Congestion Management
169(2)
Parameters Selection and Discussion
171(1)
Conclusions
172(1)
References
173(4)
Appendix A: Lagrangian Relaxation Decomposition Approach
174(3)
Dynamic Congestion Management
177(28)
J. Ma
Q. Lu
Y.H. Song
Stability Analysis and Control of Power Systems
177(4)
Stability-constrained Optimal Power Flow
181(3)
Market-based Dynamic Congestion Management [ 14--16]
184(9)
Case Studies and Analysis
193(8)
Conclusions and Future Work
201(1)
References
202(3)
Financial Instruments and Their Role in Market Dispatch and Congestion Management
205(18)
X. Wang
Y.H. Song
M. Eremia
CfDs and FTRs
206(5)
CfDs
206(1)
FTRs
207(3)
How CfDs and FTRs Hedge Price Risks
210(1)
Spot Market Dispatch and Congestion Management with Individual Revenue Adequacy Constraints
211(9)
Impact of Operating Limits on Locational Marginal Prices
211(2)
Formulation of Individual Revenue Adequacy Constraints
213(1)
Implementation
214(2)
Test Results
216(1)
System I: 5-bus System
216(1)
System II: IEEE 30-bus System
216(4)
Conclusions
220(1)
References
220(3)
Ancillary Services I: Pricing and Procurement of Reserves
223(30)
M. Rashidinejad
Y.H. Song
M.H. Javidi
Ancillary Services in the Electricity Industry
223(6)
Types of Ancillary Services
224(2)
Market for Ancillary Services
226(2)
General Considerations in England and Wales Ancillary Services Markets
228(1)
Reserve Provision and Pricing in Power Markets
229(8)
Contingency Reserves
229(1)
Reserve Procurement Mechanism
230(1)
Reserve Markets in Several Power Markets
231(1)
Reserve Markets in England and Wales
231(1)
Mandatory Frequency Response
231(1)
Commercial Ancillary Services
232(1)
Reserve Markets in the USA
232(1)
California Markets
232(1)
New York Markets
233(1)
New England Markets
234(1)
Pennsylvania New Jersey Maryland PJM Markets
234(1)
Research into Reserve Procurement and Pricing
235(2)
Joint Dispatch for Reserve Provision and Pricing
237(6)
Application of JEROD to Deal with Reserve Provision and Pricing
237(2)
Physical Constraints
239(1)
Operational Security Constraints
239(1)
Numerical Case Study
240(1)
Six-unit Test System
240(2)
Contingency Reserve Settlements
242(1)
Development of Option Pricing Mechanism for Reserve Markets
243(7)
Derivative Securities and Financial Contracts
243(1)
What Is a Derivative?
243(1)
Forward Contracts
243(1)
Futures Contracts
244(1)
Option Contracts
244(1)
Why Option Contracts are Needed for Electricity and Ancillary Services
244(1)
Option Stucture and Option Evaluation
245(2)
Application of Standard Options for Reserve Procurement and Pricing
247(1)
Case Study and Results Analysis
248(2)
Reference
250(3)
Ancillary Services II: Voltage Security and Reactive Power Management
253(28)
G.A. Taylor
S. Phichaisawat
M.R. Irving
Y.H. Song
Introduction
253(2)
Reactive Power and Voltage Control
253(1)
Monitoring and Assessment of Voltage Security
254(1)
Transition-optimised Reactive Power and Voltage Control
254(1)
Voltage Security and Congestion Management
255(1)
Reactive Power Markets and Pricing Mechanisms
255(5)
Examples of Reactive Power Markets
255(1)
England and Wales (UK)
256(1)
New York (USA)
257(1)
Australia
258(1)
Analysis of Reactive Power Markets
259(1)
Transition-optimised Reactive Power Control
260(7)
Introduction
260(1)
Algorithmic Procedure
261(1)
Objective Function
261(1)
Transition Constraints
262(1)
Solution Algorithm
262(1)
Case Studies
263(1)
Case Study I
264(1)
Case Study II
265(1)
Concluding Remarks
266(1)
Congestion Management and Voltage Security
267(10)
Introduction
267(1)
Nomenclature
267(1)
Algorithmic Procedure
268(1)
Mathematical Model
269(2)
Computational Procedures
271(2)
Computational Case Studies
273(4)
Concluding Remarks
277(1)
Acknowledgement
277(1)
References
277(4)
Load and Price Forecasting via Wavelet Transform and Neural Networks
281(36)
I.K. Yu
Y.H. Song
Load Forecasting and Conventional Techniques
282(4)
Time-series Models
282(1)
Auto-regressive (AR)
283(1)
Moving Averages (MA)
284(1)
Mixed Auto-regressive and Moving Average (ARMA)
284(1)
Regression Model
285(1)
Novel Methods for Short-term Load Forecasting
286(15)
Wavelet Transform Applications
287(1)
Wavelet Transform Analysis
287(2)
Load Forecasting Process by the Wavelet Transform
289(1)
Kohonen-neural-network-based Approach
290(1)
Architecture of the Kohonen Neural Network
291(1)
Unsupervised Learning
292(1)
STLF by a Composite Model
293(1)
Case Studies and Analysis
294(1)
Case Study by Wavelet-transform-based Model
294(4)
Classification of the Daily Load Patterns
298(1)
Numerical Results
299(2)
Electricity Price and Modelling
301(4)
Characteristics of the SMP
302(2)
SMP Models
304(1)
Forecasting the SMP
305(8)
Neural-network-based Model
305(1)
Wavelet-transform-based Model
306(1)
Combined Model
306(1)
Decomposing the SMP Data
307(1)
Predicting the Approximation
307(2)
Estimating the Detail
309(1)
Summing the Approximation and the Details
310(1)
Prediction Results and Analysis
310(1)
Predictions Results by Neural-network-based Model
310(1)
Predictions Results by Wavelet-transform-based Model
310(2)
Predictions Results by Combined Model
312(1)
Summary
313(1)
References
314(3)
Analysis of Generating Companies' Strategic Behavour
317(30)
A. Maiorano
Y.H. Song
M. Trovato
The Electricity Marketplace
318(5)
Auction Structures
318(1)
Bundling of Demand into Lots
319(2)
Sequencing of Auctions
321(1)
Pricing Rule
321(2)
Strategic Supply Functions
323(5)
Supply Constraints
326(2)
Linear Strategic Supply Functions
328(2)
Proposed Model
330(7)
Inverse Demand Function Evaluation
332(1)
Presence of Private Contracts
333(1)
Final Formulation of the Model
333(4)
Case Studies and Results Analysis
337(6)
Conclusions
343(1)
References
344(3)
Bidding Problems in Electricity Generation Markets
347(60)
Y. He
Y.H. Song
X.F. Wang
Generation Auction Markets in Electricity Markets
347(14)
Auction Mechanism
347(1)
Standard Auction Formats
347(2)
Single-round Bidding and Multi-round Bidding
349(1)
Simple Bids and Multi-part Bids
349(1)
Existing Auction Mechanism: Trading Arrangement and Pricing Mechanism
350(1)
UK Market
350(1)
PETA [ 6][ 7]
350(1)
NETA [ 8][ 9]
351(1)
California [ 10]
352(1)
PJM [ 11]
352(1)
Nord Pool [ 13]
353(1)
Australia National Electricity Market (NEM) [ 14]
354(1)
New Zealand [ 3]
354(1)
Ontario Electricity Market in Canada [ 2]
355(1)
Summary
355(1)
Market Power in Generation Auction Markets
355(1)
Getting to Know Market Power
355(2)
Measuring Market Power
357(1)
Mitigating Market Power
358(1)
Uncertainties and Risk Mitigation
359(1)
Uncertainties in Electricity Markets
359(1)
Risk Mitigation
360(1)
Decision-making and Strategies in Generation Auction Markets
361(11)
Overview of Decision-making
361(1)
Decision-making, Model and Algorithm
361(2)
Decision-making in Electricity Markets
363(1)
Decision-making in Electricity Generation Market
364(1)
Game Theory Applications in Generation Auction Market
365(1)
Basic Concept of Game Theory and Its Application in Electricity Markets
365(1)
Game-theory-based Bidding Strategies
366(1)
Optimisation-based Approaches to making Bidding strategies making
367(1)
Bidding decision-making by Optimisation-based Market Simulator
367(1)
Optimal Bidding Based on Formulation of Market Prices with Generators' Behaviours Embedded
368(3)
Application of Markov Decision Process (MDP) in Bidding Strategies
371(1)
Other Methodologies for Decision-making
372(1)
Study of Bidding Strategies Based on Bid Sensitivities in Pool-based Spot Markets
372(19)
Introduction
372(1)
Analysis of Bid Sensitivities Based on the IPOPF Model
373(2)
Bidding Strategies Based on Bid Sensitivities
375(1)
Description of the Proposed Model
375(1)
Optimal Bids
376(2)
Nash Equilibrium Process
378(1)
Bidding Strategies when Considering Coalitions
379(1)
Combinations of Potential Coalitions
379(1)
The Bidding Process Considering Coalitions
379(1)
Optimal Bids of Sub-Groups
380(4)
Case Studies and Conclusions
384(1)
Bid Sensitivities
384(2)
Bidding Processes and Optimal Bids without Coalition
386(2)
Results When Bidding under Coalition
388(2)
Conclusions
390(1)
Integrated Bidding Strategies with Optimal Response to the Probabilistic Local Marginal Prices
391(13)
Introduction
391(1)
The Proposed GencoBDS
391(2)
Three Main Modules of GencoBDS
393(1)
Security-constrained Probabilistic LMP Simulation Model
393(2)
Self-scheduling Unit Commitment Model
395(2)
MCDM Method for Optimal Offers
397(1)
Bidding Decision-making Process
398(1)
Test Results and Conclusions
399(1)
Test Results
399(4)
Conclusions
403(1)
References
404(3)
Appendix A: Notation Used in the Self-scheduling Unit Commitment Model Module
406(1)
Transmission Services Improvement by Facts Control
407(34)
Y. Xiao
X. Wang
Y.H. Song
Y.Z. Sun
Facts Solutions to Power Flow Control
408(7)
Concept of Facts Technology
408(1)
Models of Facts Devices
409(1)
Power Injection Model (PIM) of Facts Devices for ATC Enhancement
410(1)
PIM of Shunt Controller for Voltage Control
410(1)
PIM of Series Controller for Line Flow Control
410(2)
PIM of the Unified Controller for Power Flow Control
412(1)
DC Model of TCSC and TCPS for FTR Auction
413(2)
ATC Enhancement by Facts Control
415(15)
Formulated ATC Enhancement Model
418(1)
Control Variables
418(1)
Objective Function
418(1)
Operating and Control Constraints
419(2)
Implementation
421(1)
Case Studies
422(2)
Case 1: ATC Evaluation without Facts Device
424(1)
Case 2: ATC Enhancement with Control of SVC
425(3)
Case 3: ATC Enhancement with Control of SVC+TCPS
428(1)
Case 4: ATC Enhancement with Control of SVC+UPFC
428(1)
Remarks
429(1)
FTR Auction Improvement by Facts Control
430(9)
Proposed Optimal FTR Auction Model
430(2)
Case Studies
432(1)
System 1: 8-bus Test System
432(2)
System II: 30-bus Test System
434(4)
Discussion
438(1)
Remarks
439(1)
References
439(2)
Index 441


Yong-Hua Song is Professor of Electrical Energy Systems at Brunel and he also holds the Royal Academy of Engineering/Nuclear Electric/Siemens Chair of Power Systems Analysis. He is the author of over 250 journal and conference papers.