Skip to main content
Book cover

Applied Mathematics for Restructured Electric Power Systems

Optimization, Control, and Computational Intelligence

  • Book
  • © 2005

Overview

  • Coverage of global dynamic optimization of the electric power grid and modernizing the electric power grid
  • Includes supplementary material: sn.pub/extras

Part of the book series: Power Electronics and Power Systems (PEPS)

This is a preview of subscription content, log in via an institution to check access.

Access this book

eBook USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (13 chapters)

Keywords

About this book

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.

Editors and Affiliations

  • Dept. of Electrical, Computer, & Systems Engineering, Rensselaer Polytechnic Institute, Troy

    Joe H. Chow

  • Dept. of Electrical and Electronic Engineering, Hong Kong University, Hong Kong

    Felix F. Wu

  • Center for Energy Systems and Control, Howard University, Washington, DC

    James Momoh

Bibliographic Information

Publish with us