Chow, Joe H., Wu, Felix F., Momoh, James A. (Eds.)
2005, XXXII, 324 p.
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Applied Mathematics for Restructured Electric Power Systems: Optimization, Control, and Computational Intelligence consists of chapters based on work presented at a National Science Foundation workshop organized in November 2003. The theme of the workshop was the use of applied mathematics to solve challenging power system problems. The areas included control, optimization, and computational intelligence. In addition to the introductory chapter, this book includes 12 chapters written by renowned experts in their respected fields. Each chapter follows a three-part format: (1) a description of an important power system problem or problems, (2) the current practice and/or particular research approaches, and (3) future research directions. Collectively, the technical areas discussed are voltage and oscillatory stability, power system security margins, hierarchical and decentralized control, stability monitoring, embedded optimization, neural network control with adaptive critic architecture, control tuning using genetic algorithms, and load forecasting and component prediction.
This volume is intended for power systems researchers and professionals charged with solving electric and power system problems.
Content Level »Research
Keywords »algorithm - algorithms - bifurcation - calculus - computational intelligence - control - genetic algorithms - network - neural network - optimization - power systems - transmission
Applied Mathematics for Restructured Electric Power Systems.- Reactive Power and Voltage Control Issues in Electric Power Systems.- Identification of Weak Locations in Bulk Transmission Systems Using Voltage Stability Margin Index.- Bifurcation and Manifold Based Approach for Voltage and Oscillatory Stability Assessment and Control.- On-Line ATC Evaluation for Large-Scale Power Systems: Framework and Tool.- Automating Operation of Large Electric Power Systems Over Broad Ranges of Supply/Demand and Equipment Status.- Robust Control of Large Power Systems VIA Convex Optimization.- Instability Monitoring and Control of Power Systems.- Dynamic Embedded Optimization and Shooting Methods for Power System Performance Assessment.- Computational Intelligence Techniques for Control of FACTS Devices.- Placement and Coordinated Tuning of Control Devices for Capacity and Security Enhancement Using Metaheuristics.- Load Forecasting.- Independent Component Analysis Techniques for Power System Load Estimation.