Computational Intelligence in Power Engineering

  • Bijaya Ketan Panigrahi
  • Ajith Abraham
  • Swagatam Das

Part of the Studies in Computational Intelligence book series (SCI, volume 302)

Table of contents

  1. Front Matter
  2. Dusmanta Kumar Mohanta
    Pages 103-130
  3. Abbas Khosravi, Saeid Nahavandi, Doug Creighton
    Pages 131-150
  4. Krzysztof Siwek, Stanislaw Osowski
    Pages 151-169
  5. S. R. Samantaray, P. K. Dash, G. Panda
    Pages 171-198
  6. Kyeon Hur, Surya Santoso
    Pages 199-234
  7. M. R. AlRashidi, M. F. AlHajri, A. K. Al-Othman, K. M. El-Naggar
    Pages 295-324
  8. S. P. Ghoshal, A. Chatterjee, V. Mukherjee
    Pages 325-366
  9. Ashu Verma, P. R. Bijwe, B. K. Panigrahi
    Pages 367-379
  10. Back Matter

About this book

Introduction

Computational Intelligence (CI) is one of the most important powerful tools for research in the diverse fields of engineering sciences ranging from traditional fields of civil, mechanical engineering to vast sections of electrical, electronics and computer engineering and above all the biological and pharmaceutical sciences. The existing field has its origin in the functioning of the human brain in processing information, recognizing pattern, learning from observations and experiments, storing and retrieving information from memory, etc. In particular, the power industry being on the verge of epoch changing due to deregulation, the power engineers require Computational intelligence tools for proper planning, operation and control of the power system. Most of the CI tools are suitably formulated as some sort of optimization or decision making problems. These CI techniques provide the power utilities with innovative solutions for efficient analysis, optimal operation and control and intelligent decision making. This edited volume deals with different CI techniques for solving real world Power Industry problems. The technical contents will be extremely helpful for the researchers as well as the practicing engineers in the power industry.

Keywords

artificial intelligence computational intelligence control electronics evolution fuzzy intelligence learning linear optimization machine learning mechanical engineering neural network neural networks optimization power systems

Editors and affiliations

  • Bijaya Ketan Panigrahi
    • 1
  • Ajith Abraham
    • 2
  • Swagatam Das
    • 3
  1. 1.Indian Institute of TechnologyNew DelhiIndia
  2. 2.Jadavpur UniversityCalcuttaIndia
  3. 3.Norwegian University of Science and TechnologyTrondheimNorway

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-14013-6
  • Copyright Information Springer-Verlag Berlin Heidelberg 2010
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-14012-9
  • Online ISBN 978-3-642-14013-6
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • About this book