Artificial Intelligence Techniques in Power Systems
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Artificial Intelligence Techniques in Power Systems: (Energy Engineering)

Artificial Intelligence Techniques in Power Systems: (Energy Engineering)


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About the Book

Research in artificial intelligence has developed many techniques and methodologies that can be either adapted or used directly to solve complex power system problems. A variety of such problems are covered in this book including reactive power control, alarm analysis, fault diagnosis, protection systems and load forecasting. Methods such as knowledge-based (expert) systems, fuzzy logic, neural networks and genetic algorithms are all first introduced and then investigated in terms of their applicability in the power systems field. The book, therefore, serves as both an introduction to the use of artificial intelligence techniques for those from a power systems background and as an overview of the power systems implementation area for those from an artificial intelligence computing or control background. It is structured so that it is suitable for various levels of reader, covering basic principles as well as applications and case studies. The most popular methods and the most fruitful application fields are considered in more detail. The book contains contributions from top international authors and will be an extremely useful text for all those with an interest in the field.

Table of Contents:
Chapter 1: Artificial intelligence techniques in power systems Chapter 2: Advanced knowledge engineering techniques with applications to electric power systems Chapter 3: Object-oriented design and implementation of power system analysis software Chapter 4: Fuzzy logic and hybrid systems Chapter 5: Alarm analysis Chapter 6: Artificial intelligence techniques for voltage control Chapter 7: AI for protection systems Chapter 8: Artificial neural networks for static security assessment Chapter 9: Knowledge based systems for condition monitoring Chapter 10: Scheduling maintenance of electrical power transmission networks using genetic programming Chapter 11: Neuro-expert system applications in power systems Chapter 12: Intelligent systems for demand forcasting Chapter 13: A practical application and implementation of adaptive techniques using neural networks into autoreclose protection and system control

About the Author :
Kevin Warwick is Professor of Cybernetics at the University of Reading, UK. He previously held positions at Oxford, Newcastle and Warwick Universities and has higher Doctorates from both Imperial College, London, and the Czech Academy of Sciences, Prague. He was an Honorary Editor of the IEE Proceedings on Control Theory and Applications and is actively involved in research into artificial intelligence, control and robotics. Arthur Ekwue obtained a BSc (Eng) degree in Electrical Engineering from the University of Nigeria, Nsukka. He came to Imperial College in 1979 and was awarded a PhD degree in Power Systems in 1982. He obtained the MBA degree in 1994 from City University. Dr Ekwue is a Chartered Engineer and currently with National Grid Company plc's Technology and Science Division as the Senior Project Engineer responsible for artificial intelligence applications within the Power Systems and Business Modelling Section. Rag Aggarwal received his BEng and PhD degrees in Electrical Engineering from the University of Liverpool and joined the University of Bath in 1973 where he is now a reader in the Power and Energy Systems Group. He is the author of over 200 refereed papers and the recipient of two Learned Society premium awards for papers published in IEE journals. His areas of research are power system modelling, digital protection, fibre optics and AI in power system protection and control.

Review :
'This book is a useful introduction to the field of AI for power engineers [and] presents several meaningful case-studies that will help practioners in deciding which directions are worthy of further investigation and near-term success.' IEEE Computer Applications in Power


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Product Details
  • ISBN-13: 9781849191722
  • Publisher: Institution of Engineering and Technology
  • Publisher Imprint: Institution of Engineering and Technology
  • Language: English
  • ISBN-10: 1849191727
  • Publisher Date: 23 Sep 2011
  • Binding: Digital download and online
  • Series Title: Energy Engineering


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