Automatic Learning Techniques in Power Systems

  • Louis A. Wehenkel

Table of contents

  1. Front Matter
    Pages i-xxix
  2. Introduction

    1. Louis A. Wehenkel
      Pages 1-19
  3. Automatic Learning Methods

    1. Front Matter
      Pages 21-21
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      Pages 23-46
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      Pages 47-70
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      Pages 71-98
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      Pages 99-144
    6. Louis A. Wehenkel
      Pages 145-157
  4. Application of Automatic Learning to Security Assessment

    1. Front Matter
      Pages 159-159
    2. Louis A. Wehenkel
      Pages 165-174
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      Pages 175-192
    4. Louis A. Wehenkel
      Pages 193-228
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      Pages 229-233
    6. Louis A. Wehenkel
      Pages 235-243
  5. Automatic Learning Applications in Power Systems

    1. Front Matter
      Pages 245-245
    2. Louis A. Wehenkel
      Pages 247-255
  6. Back Matter
    Pages 257-280

About this book


Automatic learning is a complex, multidisciplinary field of research and development, involving theoretical and applied methods from statistics, computer science, artificial intelligence, biology and psychology. Its applications to engineering problems, such as those encountered in electrical power systems, are therefore challenging, while extremely promising. More and more data have become available, collected from the field by systematic archiving, or generated through computer-based simulation. To handle this explosion of data, automatic learning can be used to provide systematic approaches, without which the increasing data amounts and computer power would be of little use.
Automatic Learning Techniques in Power Systems is dedicated to the practical application of automatic learning to power systems. Power systems to which automatic learning can be applied are screened and the complementary aspects of automatic learning, with respect to analytical methods and numerical simulation, are investigated.
This book presents a representative subset of automatic learning methods - basic and more sophisticated ones - available from statistics (both classical and modern), and from artificial intelligence (both hard and soft computing). The text also discusses appropriate methodologies for combining these methods to make the best use of available data in the context of real-life problems.
Automatic Learning Techniques in Power Systems is a useful reference source for professionals and researchers developing automatic learning systems in the electrical power field.


Counter Soft Computing artificial intelligence artificial neural network computer development intelligence learning model network neural networks power systems simulation tables

Authors and affiliations

  • Louis A. Wehenkel
    • 1
  1. 1.National Fund for Scientific ResearchUniversity of Liège — Institut MontefioreLiègeBelgium

Bibliographic information

  • DOI
  • Copyright Information Kluwer Academic Publishers 1998
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-7489-3
  • Online ISBN 978-1-4615-5451-6
  • About this book