Title Page	3
	Copyright Page	4
	Preface	5
	Table of Contents	7
	1 Introduction	12
	1.1 Principles of Deregulation	12
	1.2 Overview of Deregulation Worldwide	13
	1.2.1 Regulated vs Deregulated	14
	1.2.2 Typical Electricity Markets	16
	1.3 Uncertainties in a Power System	17
	1.3.1 Load Modeling Issues	18
	1.3.2 Distributed Generation	21
	1.4 Situational Awareness	21
	1.5 Control Performance	22
	1.5.1 Local Protection and Control	23
	1.5.2 Centralized Protection and Control	25
	1.5.3 Possible Coordination Problem in the Existing Protection and Control System	26
	1.5.4 Two Scenarios to Illustrate the Coordination Issues among Protection and Control Systems	27
	1) Load Shedding or Generator Tripping	27
	2) Zone 3 Protection	29
	1.6 Summary	30
	References	30
	2 Fundamentals of Emerging Techniques	33
	2.1 Power System Cascading Failure and Analysis Techniques	33
	2.2 Data Mining and Its Application in Power System Analysis	37
	2.3 Grid Computing	39
	2.4 Probabilistic vs Deterministic Approaches	41
	2.5 Phasor Measurement Units	44
	2.6 Topological Methods	45
	2.7 Power System Vulnerability Assessment	46
	2.8 Summary	49
	3 Data Mining Techniques and Its Application in Power Industry	55
	3.1 Introduction	55
	3.2 Fundamentals of Data Mining	56
	3.3 Correlation, Classification and Regression	57
	3.4 Available Data Mining Tools	59
	3.5 Data Mining based Market Data Analysis	61
	3.5.1 Introduction to Electricity Price Forecasting	61
	3.5.2 The Price Spikes in an Electricity Market	62
	3.5.3 Framework for Price Spike Forecasting	64
	3.5.4 Problem Formulation of Interval Price Forecasting	73
	3.5.5 The Interval Forecasting Approach	75
	3.6 Data Mining based Power System Security Assessment	80
	3.6.1 Background	82
	3.6.2 Network Pattern Mining and Instability Prediction	84
	3.7 Case Studies	89
	3.7.2 Case Study on Interval Price Forecasting	93
	3.7.3 Case Study on Security Assessment	99
	3.8 Summary	102
	References	102
	4 Grid Computing	105
	4.1 Introduction	105
	4.2 Fundamentals of Grid Computing	106
	4.2.1 Architecture	107
	4.2.2 Features and Functionalities	108
	4.2.3 Grid Computing vs Parallel and Distributed Computing	110
	4.3 Commonly used Grid Computing Packages	111
	4.3.1 Available Packages	111
	4.3.2 Projects	112
	4.3.3 Applications in Power Systems	114
	4.4 Grid Computing based Security Assessment	115
	4.5 Grid Computing based Reliability Assessment	117
	4.6 Grid Computing based Power Market Analysis	118
	4.7 Case Studies	119
	4.7.1 Probabilistic Load Flow	119
	4.7.2 Power System Contingency Analysis	121
	4.7.3 Performance Comparison	121
	4.8 Summary	123
	5 Probabilistic vs Deterministic Power System Stability and Reliability Assessment	126
	5.1 Introduction	126
	5.2 Identify the Needs for the Probabilistic Approach	127
	5.2.1 Power System Stability Analysis	127
	5.2.2 Power System Reliability Analysis	128
	5.2.3 Power System Planning	129
	5.3 Available Tools for Probabilistic Analysis	130
	5.3.1 Power System Stability Analysis	130
	5.3.2 Power System Reliability Analysis	132
	5.3.3 Power System Planning	132
	5.4 Probabilistic Stability Assessment	134
	5.4.1 Probabilistic Transient Stability Assessment Methodology	134
	5.4.2 Probabilistic Small Signal Stability Assessment Methodology	136
	5.5 Probabilistic Reliability Assessment	137
	5.5.1 Power System Reliability Assessment	137
	5.5.2 Probabilistic Reliability Assessment Methodology	140
	5.6 Probabilistic System Planning	144
	5.6.1 Candidates Pool Construction	144
	5.6.2 Feasible Options Selection	145
	5.6.3 Reliability and Cost Evaluation	145
	5.6.4 Final Adjustment	145
	5.7 Case Studies	146
	5.7.1 A Probabilistic Small Signal Stability Assessment Example	146
	5.7.2 Probabilistic Load Flow	149
	5.8 Summary	151
	References	152
	6 Phasor Measurement Unit and Its Applicationin Modern Power Systems	155
	6.1 Introduction	155
	6.2 State Estimation	159
	6.2.1 An Overview	159
	6.2.2 Weighted Least Squares Method	160
	6.2.3 Enhanced State Estimation	162
	6.3 Stability Analysis	165
	6.3.1 Voltage and Transient Stability	166
	6.3.2 Small Signal Stability—Oscillations	168
	6.4 Event Identification and Fault Location	170
	6.5 Enhance Situation Awareness	172
	6.6 Model Validation	175
	6.7 Case Study	177
	6.7.1 Overview	178
	6.7.2 Formulation of Characteristic Ellipsoids	178
	6.7.3 Geometry Properties of Characteristic Ellipsoids	180
	6.7.4 Interpretation Rules for Characteristic Ellipsoids	181
	6.7.5 Simulation Results	183
	6.8 Conclusion	187
	References	187
	7 Conclusions and Future Trends in Emerging Techniques	193
	7.1 Identified Emerging Techniques	193
	7.2 Trends in Emerging Techniques	194
	7.3 Further Reading	195
	7.3.1 Economic Impact of Emission Trading Schemes and Carbon Production Reduction Schemes	195
	7.3.2 Power Generation based on Renewable Resources such as Wind	197
	7.3.3 Smart Grid	198
	7.4 Summary	199
	References	199
	Appendix	202
	A.1 Weibull Distribution	202
	A1.1 An Illustrative Example	203
	A.2 Eigenvalues and Eigenvectors	204
	A.3 Eigenvalues and Stability	205
	References	207
	Index	208