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E-raamat: Artificial Intelligence in Power System Optimization

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  • Formaat: 520 pages
  • Ilmumisaeg: 19-Apr-2016
  • Kirjastus: Science Publishers,U.S.
  • Keel: eng
  • ISBN-13: 9781466573420
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Artificial Intelligence in Power System OptimizationSuurem pilt
  • Formaat: 520 pages
  • Ilmumisaeg: 19-Apr-2016
  • Kirjastus: Science Publishers,U.S.
  • Keel: eng
  • ISBN-13: 9781466573420
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"With the considerable increase of AI applications, AI is being increasingly used to solve optimization problems in engineering. In the past two decades, the applications of artificial intelligence in power systems have attracted much research. This bookcovers the current level of applications of artificial intelligence to the optimization problems in power systems. This book serves as a textbook for graduate students in electric power system management and is also be useful for those who are interestedin using artificial intelligence in power system optimization"--

Ongsakul (energy fields, Asian Institute of Technology, Thailand) and Vo (electrical and electronic engineering, Ho Chi Minh City U. of Technology, Vietnam) discuss recent applications of artificial intelligence to optimization problems in power systems both before and after deregulation. They provide graduate students of electric power systems management the basic knowledge of different optimization problem encountered in operating a utility and in negotiating the electricity market. They cover economic dispatch, unit commitment, hydrothermal scheduling, optimal power flow, optimal reactive power dispatch, and available transfer capacity. Annotation ©2013 Book News, Inc., Portland, OR (booknews.com)

With the considerable increase of AI applications, AI is being increasingly used to solve optimization problems in engineering. In the past two decades, the applications of artificial intelligence in power systems have attracted much research. This book covers the current level of applications of artificial intelligence to the optimization problems in power systems. This book serves as a textbook for graduate students in electric power system management and is also be useful for those who are interested in using artificial intelligence in power system optimization.

Preface v
1 Introduction
1(10)
1.1 Importance of Power System Optimization
1(2)
1.2 Artificial Intelligence as a New Trend in Optimization Problems
3(3)
1.3 Artificial Intelligence Applications in Power Systems
6(1)
1.4 Overview of the Book
7(2)
1.5 References
9(2)
2 Economic Dispatch
11(107)
2.1 Introduction
11(1)
2.2 Generator Incremental Cost Curve
12(1)
2.3 Economic Dispatch Problem Formulation without Regarding Loss
13(7)
2.4 Economic Dispatch Considering Transmission Losses
20(9)
2.5 Economic Dispatch with Ramp Rate Constraint
29(2)
2.6 Fuel Constrained Economic Dispatch
31(11)
2.7 Economic Dispatch Considering Emissions
42(7)
2.8 Economic Dispatch with Transmission Constraint
49(10)
2.9 Economic Dispatch with Non-smooth Cost Functions
59(18)
2.10 Combined Heat and Power Economic Dispatch
77(9)
2.11 Hydrothermal Economic Dispatch
86(10)
2.12 Optimal Power Dispatch in a Competitive Electricity Supply Industry
96(9)
2.13 Summary
105(1)
2.14 Problems for Exercise
106(7)
2.15 References
113(5)
3 Unit Commitment
118(114)
3.1 Introduction
118(9)
3.2 Unit Commitment Problem Formulation
127(3)
3.3 Unit Commitment Solution Methods
130(61)
3.4 Constrained Unit Commitment
191(19)
3.5 Security Constrained Unit Commitment
210(9)
3.6 Price-based Unit Commitment
219(8)
3.7 Summary
227(1)
3.8 Problems
227(3)
3.9 References
230(2)
4 Hydrothermal Scheduling
232(60)
4.1 Introduction
232(1)
4.2 Hydroelectric Plant Model
233(1)
4.3 Hydrothermal Scheduling Formulation
233(2)
4.4 Hydrothermal Scheduling Methods
235(9)
4.5 Hydroelectric Units in Series
244(1)
4.6 Pumped Storage Hydroelectric Plants
245(1)
4.7 Problem Formulation for Hydrothermal Scheduling for Both Hydroelectric and Pumped Storage Hydroelectric Plants
246(3)
4.8 Solution Methods for Hydrothermal Scheduling Including Pumped Storage Hydroelectric Plants
249(39)
4.9 Summary
288(1)
4.10 Problems
289(1)
4.11 References
290(2)
5 Optimal Power Flow
292(25)
5.1 Introduction
292(1)
5.2 Optimal Power Flow Problem Formulation
293(2)
5.3 Optimal Real Power Dispatch with Network Limit Constraints
295(9)
5.4 Neural Network Application to Optimal Power Flow
304(3)
5.5 Particle Swarm Optimization for Optimal Power Flow
307(5)
5.6 Summary
312(1)
5.7 Problems
312(2)
5.8 References
314(3)
6 Optimal Reactive Power Dispatch
317(38)
6.1 Introduction
317(1)
6.2 Reactive Power in Power Systems
318(15)
6.3 Conventional Optimal Reactive Power Dispatch
333(6)
6.4 Optimal Reactive Power Dispatch in Deregulated Electricity Markets
339(9)
6.5 TVAC-PSO based Optimal Reactive Power Dispatch under Deregulated Electricity Market Conditions
348(4)
6.6 Summary
352(1)
6.7 Problems
352(1)
6.8 References
353(2)
7 Available Transfer Capability
355(60)
7.1 Introduction
355(1)
7.2 Transmission Transfer Capability Concepts
356(3)
7.3 Available Transfer Capability Principles
359(1)
7.4 Available Transfer Capability Definition and Determination
360(7)
7.5 Methodologies to Calculate ATC
367(3)
7.6 Available Transfer Capability Calculation
370(6)
7.7 Calculation of Total Transfer Capability by Evolutionary Programming
376(8)
7.8 Total Transfer Capability Enhancement by Hybrid Evolutionary Algorithm
384(9)
7.9 Optimal Placement of Multi-type Facts Devices for ATC Enhancement Using HEA
393(12)
7.10 Summary
405(1)
7.11 Problems
406(2)
7.12 References
408(7)
Appendix A Mathematical Model Derivations 415(25)
Appendix B Data of Example Systems 440(8)
Appendix C Results of Examples 448(22)
Appendix D Tips for Programming in Matlab 470(23)
Index 493(4)
Color Plate Section 497
Weerakorn Ongsakul, Vo Ngoc Dieu
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