Book Description:
This book presents state of the art applications of artificial intelligence in energy and renewable energy systems design and modeling. It covers such topics as solar energy, wind energy, biomass and hydrogen as well as building services systems, power generation systems, combustion processes and refrigeration. In all these areas applications of artificial intelligence methods such as artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above, called hybrid systems, are included. This book is intended for a wide audience ranging from the undergraduate level up to the research academic and industrial communities dealing with modeling and performance prediction of energy and renewable energy systems.

Table of Contents:
Chapter Availability

Individual chapters are available for $25 each by sending an email to novascience@earthlink.net. Nova will provide the chapter for your easy downloading or send it as an email attachment if you prefer.

Preface

Chapter 1.-Introduction to artificial intelligence technology; pp. 1-46
(Soteris Kalogirou)

Chapter 2.-Artificial neural networks for meteorological variables pertained to energy and renewable energy applications; pp. 47-82
(Silas Michaelides, Filippos Tymvios, Soteris Kalogirou)

Chapter 3.-Artificial neural networks in solar thermal energy systems; pp. 83-130
(Sylvain Lalot)

Chapter 4.-Artificial neural networks and genetic algorithms for the optimization of solar thermal systems; pp. 131-162
(Soteris Kalogirou)

Chapter 5.-Artificial neural networks applied in PV systems and solar radiation; pp. 163-200
(Leocadio Hontoria, Jorge Aguilera, Florencia Almonacid, Gustavo Nofuentes, Pedro Zufiria)

Chapter 6.-Application of control algorithms for wind speed prediction and active power generation; pp. 201-233
(Arantxa Tapia, Gerardo Tapia, Patxi Flores)

Chapter 7.-Neuro-fuzzy Hammerstein model based predictive control of a solid oxide fuel cell; pp. 235-268
(Francisco Jurado)

Chapter 8.-The application of fuzzy systems to control and modeling of building systems; pp. 269-307
(Chris Underwood)

Chapter 9.-Application of computational intelligence techniques to architectural and building acoustics; pp. 309-338
(Jingfeng Xu, Joseph Nannariello, Fergus Fricke)

Chapter 10.-Active learning strategies for the neural estimation of engine maps; pp. 339-362
(Marta Neve, Giuseppe De Nicolao)

Chapter 11.-The application of artificial intelligence techniques in combustion systems; pp. 363-394
(John Ward, Chee-Keong Tan, Alex Z.S. Chong, Steven Wilcox)

Chapter 12.-Learning control of fluidized-bed combustion processes for power plants; pp. 395-438
(Enso Ikonen, Jeno Kovács)

Chapter 13.-Application of artificial intelligence techniques for the reduction of energy consumption of refrigeration systems; pp. 439-457