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E-raamat: Emerging Techniques in Power System Analysis

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  • Formaat: PDF+DRM
  • Ilmumisaeg: 01-Jun-2010
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Keel: eng
  • ISBN-13: 9783642042829
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Emerging Techniques in Power System AnalysisSuurem pilt
  • Formaat: PDF+DRM
  • Ilmumisaeg: 01-Jun-2010
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Keel: eng
  • ISBN-13: 9783642042829
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"Emerging Techniques in Power System Analysis" identifies the new challenges facing the power industry following the deregulation. The book presents emerging techniques including data mining, grid computing, probabilistic methods, phasor measurement unit (PMU) and how to apply those techniques to solving the technical challenges.



The book is intended for engineers and managers in the power industry, as well as power engineering researchers and graduate students.



Zhaoyang Dong is an associate professor at the Department of Electrical Engineering, The Hong Kong Polytechnic University, China. Pei Zhang is program manager at the Electric Power Research Institute (EPRI), USA.
1 Introduction
1(22)
1.1 Principles of Deregulation
1(1)
1.2 Overview of Deregulation Worldwide
2(4)
1.2.1 Regulated vs Deregulated
3(2)
1.2.2 Typical Electricity Markets
5(1)
1.3 Uncertainties in a Power System
6(4)
1.3.1 Load Modeling Issues
7(3)
1.3.2 Distributed Generation
10(1)
1.4 Situational Awareness
10(1)
1.5 Control Performance
11(8)
1.5.1 Local Protection and Control
12(2)
1.5.2 Centralized Protection and Control
14(1)
1.5.3 Possible Coordination Problem in the Existing Protection and Control System
15(1)
1.5.4 Two Scenarios to Illustrate the Coordination Issues Among Protection and Control Systems
16(3)
1.6 Summary
19(4)
References
19(4)
2 Fundamentals of Emerging Techniques
23(22)
2.1 Power System Cascading Failure and Analysis Techniques
23(4)
2.2 Data Mining and its Application in Power System Analysis
27(2)
2.3 Grid Computing
29(2)
2.4 Probabilistic vs Deterministic Approaches
31(3)
2.5 Phasor Measurement Units
34(1)
2.6 Topological Methods
35(1)
2.7 Power System Vulnerability Assessment
36(3)
2.8 Summary
39(6)
References
39(6)
3 Data Mining Techniques and its Application in Power Industry
45(50)
3.1 Introduction
45(1)
3.2 Fundamentals of Data Mining
46(1)
3.3 Correlation, Classification and Regression
47(2)
3.4 Available Data Mining Tools
49(2)
3.5 Data Mining based Market Data Analysis
51(19)
3.5.1 Introduction to Electricity Price Forecasting
51(1)
3.5.2 The Price Spikes in an Electricity Market
52(2)
3.5.3 Framework for Price Spike Forecasting
54(9)
3.5.4 Problem Formulation of Interval Price Forecasting
63(2)
3.5.5 The Interval Forecasting Approach
65(5)
3.6 Data Mining based Power System Security Assessment
70(9)
3.6.1 Background
72(2)
3.6.2 Network Pattern Mining and Instability Prediction
74(5)
3.7 Case Studies
79(13)
3.7.1 Case Study on Price Spike Forecasting
80(3)
3.7.2 Case Study on Interval Price Forecasting
83(6)
3.7.3 Case Study on Security Assessment
89(3)
3.8 Summary
92(3)
References
92(3)
4 Grid Computing
95(22)
4.1 Introduction
95(1)
4.2 Fundamentals of Grid Computing
96(5)
4.2.1 Architecture
97(1)
4.2.2 Features and Functionalities
98(2)
4.2.3 Grid Computing vs Parallel and Distributed Computing
100(1)
4.3 Commonly used Grid Computing Packages
101(4)
4.3.1 Available Packages
101(1)
4.3.2 Projects
102(2)
4.3.3 Applications in Power Systems
104(1)
4.4 Grid Computing based Security Assessment
105(2)
4.5 Grid Computing based Reliability Assessment
107(1)
4.6 Grid Computing based Power Market Analysis
108(1)
4.7 Case Studies
109(4)
4.7.1 Prohabilistic Load Flow
109(2)
4.7.2 Power System Contingency Analysis
111(1)
4.7.3 Performance Comparison
111(2)
4.8 Summary
113(4)
References
113(4)
5 Probabilstic vs Deterministic Power System Stability and Reliability Assesment
117(30)
5.1 Introduction
117(1)
5.2 Identify the Needs for the Probabilistic Approach
118(3)
5.2.1 Power System Stability Analysis
118(1)
5.2.2 Power System Reliability Analysis
119(1)
5.2.3 Power System Planning
120(1)
5.3 Available Tools for Probabilistic Analysis
121(4)
5.3.1 Power System Stability Analysis
121(2)
5.3.2 Power System Reliability Analysis
123(1)
5.3.3 Power System Planning
123(2)
5.4 Probabilistic Stability Assessment
125(3)
5.4.1 Probabilistic Transient Stability Assessment Methodology
125(2)
5.4.2 Probabilistic Small Signal Stability Assessment Methodology
127(1)
5.5 Probabilistic Reliability Assessment
128(7)
5.5.1 Power System Reliability Assessment
128(3)
5.5.2 Probabilistic Reliability Assessment Methodology
131(4)
5.6 Probabilistic System Planning
135(2)
5.6.1 Candidates Pool Construction
136(1)
5.6.2 Feasible Options Selection
136(1)
5.6.3 Reliability and Cost Evaluation
136(1)
5.6.4 Final Adjustment
136(1)
5.7 Case Studies
137(5)
5.7.1 A Probabilistic Small Signal Stability Assessment Example
137(3)
5.7.2 Probabilistic Load Flow
140(2)
5.8 Summary
142(5)
References
143(4)
6 Phasor Measurement Unit and its Application in Modern Power Systems
147(38)
6.1 Introduction
147(4)
6.2 State Estimation
151(6)
6.2.1 An Overview
151(1)
6.2.2 Weighted Least Squares Method
152(2)
6.2.3 Enchanced State Estimation
154(3)
6.3 Stability Analysis
157(5)
6.3.1 Voltage and Transient Stability
158(2)
6.3.2 Small Signal Stability---Oscillations
160(2)
6.4 Event Identification and Fault Location
162(2)
6.5 Enhance Situation Awareness
164(3)
6.6 Model Validation
167(2)
6.7 Case Study
169(10)
6.7.1 Overview
170(1)
6.7.2 Formulation of Characteristic Ellipsoids
170(2)
6.7.3 Geometry Properties of Characteristic Ellipsoids
172(1)
6.7.4 Interpretation Rules for Characteristic Ellipsoids
173(2)
6.7.5 Simulation Results
175(4)
6.8 Conclusion
179(6)
References
179(6)
7 Conclusions and Future Trends in Emerging Techniques
185(10)
7.1 Identified Emerging Techniques
185(1)
7.2 Trends in Emerging Techniques
186(1)
7.3 Further Reading
187(4)
7.3.1 Economic Impact of Emission Trading Schemes and Carbon Production Reduction Schemes
187(2)
7.3.2 Power Generation based on Renewable Resources such as Wind
189(1)
7.3.3 Smart Grid
190(1)
7.4 Summary
191(4)
References
191(4)
Appendix
195(6)
A.1 Weibull Distribution
195(2)
A1.1 An Illustrative Example
196(1)
A.2 Eigenvalues and Eigenvectors
197(1)
A.3 Eigenvalues and Stability
198(3)
References
200(1)
Index 201
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