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.

Front Matter
1 Introduction
  1.1 Principles of Deregulation
  1.2 Overview of Deregulation Worldwide
   1.2.1 Regulated vs Deregulated
   1.2.2 Typical Electricity Markets
  1.3 Uncertainties in a Power System
   1.3.1 Load Modeling Issues.
   1.3.2 Distributed Generation
  1.4 Situational Awareness
  1.5 Control Performance
   1.5.1 Local Protection and Control
   1.5.2 Centralized Protection and Control
   1.5.3 Possible Coordination Problem in the Existing Protection and Control System
   1.5.4 Two Scenarios to Illustrate the Coordination Issues Among Protection and Control Systems
  1.6 Summary
  References
2 Fundamentals of Emerging Techniques
  2.1 Power System Cascading Failure and Analysis Techniques
  2.2 Data Mining and Its Application in Power System Analysis
  2.3 Grid Computing
  2.4 Probabilistic vs Deterministic Approaches
  2.5 Phasor Measurement Units
  2.6 Topological Methods
  2.7 Power System Vulnerability Assessment
  2.8 Summary
  References
3 Data Mining Techniques and Its Application in Power Industry
  3.1 Introduction
  3.2 Fundamentals of Data Mining
  3.3 Correlation, Classification and Regression
  3.4 Available Data Mining Tools
  3.5 Data Mining based Market Data Analysis
   3.5.1 Introduction to Electricity Price Forecasting
   3.5.2 The Price Spikes in an Electricity Market
   3.5.3 Framework for Price Spike Forecasting
   3.5.4 Problem Formulation of Interval Price Forecasting
   3.5.5 The Interval Forecasting Approach
  3.6 Data Mining based Power System Security Assessment
   3.6.1 Background
   3.6.2 Network Pattern Mining and Instability Prediction
  3.7 Case Studies
   3.7.1 Case Study on Price Spike Forecasting
   3.7.2 Case Study on Interval Price Forecasting
   3.7.3 Case Study on Security Assessment
  3.8 Summary
  References
4 Grid Computing
  4.1 Introduction
  4.2 Fundamentals of Grid Computing
   4.2.1 Architecture
   4.2.2 Features and Functionalities
   4.2.3 Grid Computing vs Parallel and Distributed Computing
  4.3 Commonly used Grid Computing Packages
   4.3.1 Available Packages
   4.3.2 Projects
   4.3.3 Applications in Power Systems
  4.4 Grid Computing based Security Assessment
  4.5 Grid Computing based Reliability Assessment
  4.6 Grid Computing based Power Market Analysis
  4.7 Case Studies
   4.7.1 Probabilistic Load Flow
   4.7.2 Power System Contingency Analysis
   4.7.3 Performance Comparison
  4.8 Summary
  References
5 Probabilistic vs Deterministic Power System Stability and Reliability Assessment
  5.1 Introduction
  5.2 Identify the Needs for The Probabilistic Approach
   5.2.1 Power System Stability Analysis
   5.2.2 Power System Reliability Analysis
   5.2.3 Power System Planning
  5.3 Available Tools for Probabilistic Analysis
   5.3.1 Power System Stability Analysis
   5.3.2 Power System Reliability Analysis
   5.3.3 Power System Planning
  5.4 Probabilistic Stability Assessment
   5.4.1 Probabilistic Transient Stability Assessment Methodology
   5.4.2 Probabilistic Small Signal Stability Assessment Methodology
  5.5 Probabilistic Reliability Assessment
   5.5.1 Power System Reliability Assessment
   5.5.2 Probabilistic Reliability Assessment Methodology
  5.6 Probabilistic System Planning
   5.6.1 Candidates Pool Construction
   5.6.2 Feasible Options Selection
   5.6.3 Reliability and Cost Evaluation
   5.6.4 Final Adjustment
  5.7 Case Studies
   5.7.1 A Probabilistic Small Signal Stability Assessment Example
   5.7.2 Probabilistic Load Flow
  5.8 Summary
  References
6 Phasor Measurement Unit and Its Application in Modern Power Systems
  6.1 Introduction
  6.2 State Estimation
   6.2.1 An Overview
   6.2.2 Weighted Least Squares Method
   6.2.3 Enhanced State Estimation
  6.3 Stability Analysis
   6.3.1 Voltage and Transient Stability
   6.3.2 Small Signal Stability—Oscillations
  6.4 Event Identification and Fault Location
  6.5 Enhance Situation Awareness
  6.6 Model Validation
  6.7 Case Study
   6.7.1 Overview
   6.7.2 Formulation of Characteristic Ellipsoids
   6.7.3 Geometry Properties of Characteristic Ellipsoids
   6.7.4 Interpretation Rules for Characteristic Ellipsoids
   6.7.5 Simulation Results
  6.8 Conclusion
  References
7 Conclusions and Future Trends in Emerging Techniques
  7.1 Identified Emerging Techniques
  7.2 Trends in Emerging Techniques
  7.3 Further Reading
   7.3.1 Economic Impact of Emission Trading Schemes and Carbon Production Reduction Schemes
   7.3.2 Power Generation based on Renewable Resources such as Wind
   7.3.3 Smart Grid
  7.4 Summary
  References
Appendix
  A.1 Weibull Distribution
  A1.1 An Illustrative Example
  A.2 Eigenvalues and Eigenvectors
  A.3 Eigenvalues and Stability
  References
Index