
Soft Computing in Renewable Energy Technologies
- 227 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Soft Computing in Renewable Energy Technologies
About this book
This book addresses and disseminates state-of-the-art research and development in the applications of soft computing techniques for renewable energy systems. It covers topics such as solar energy, wind energy, and solar concentrator technologies, as well as building systems and power generation systems. In all these areas, applications of soft computing methods such as artificial neural networks, genetic algorithms, particle swarm optimization, cuckoo search, fuzzy logic, and a combination of these, called hybrid systems, are included. This book is a source for students interested in the fields of renewable energy and the application of the soft computing. In addition, our book can be considered as a reference for researchers and academics since it will include applications of soft computing in different renewable energy systems.
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Information
Table of contents
- Cover
- Half Title
- Title
- Copyright
- Contents
- Preface
- About the Editors
- List of Contributors
- 1 Introduction to Renewable Energy Technologies
- 2 Soft Computing Techniques in Solar PV Energy Systems: A Review
- 3 Parameter Identification for Three-Diode Model Using the Tiki Taka Algorithm
- 4 Comparative Analysis of Conventional and Cuckoo Search MPPT Algorithms in PV Systems under Uniform Condition
- 5 Overview of Solar Concentrator Technologies and Their Role in the Development of CSP Plants
- 6 Soft Computing Techniques in Wind Conversion Systems: A Review
- 7 Artificial Neural Network-Based MPPT Controller for Variable-Speed Wind Energy Conversion System
- 8 Enhancing Wind Energy Harnessing with an Intelligent MPPT Controller Using African Vulture Optimization Algorithm
- 9 Renewable Energy Powered Switched Reluctance Motor for Marine Propulsion System Using Soft Computing Techniques
- Index
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