Modeling Identification And Control Methods In Renewable Energy Systems
Download Modeling Identification And Control Methods In Renewable Energy Systems PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Modeling Identification And Control Methods In Renewable Energy Systems book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Modeling, Identification and Control Methods in Renewable Energy Systems
Most of the research and experiments in the fields of modeling and control systems have spent significant efforts to find rules from various complicated phenomena by principles, observations, measured data, logic derivations. The rules are normally summarized as concise and quantitative expressions or “models”. “Identification” provides mechanisms to establish the models and “control” provides mechanisms to improve system performances. This book reflects the relevant studies and applications in the area of renewable energies, with the latest research from interdisciplinary theoretical studies, computational algorithm development to exemplary applications. It discusses how modeling and control methods such as recurrent neural network, Pitch Angle Control, Fuzzy control, Sliding Mode Control and others are used in renewable systems. It covers topics as photovoltaic systems, wind turbines, maximum power point tracking, batteries for renewable energies, solar energy, thermal energy and so on. This book is edited and written by leading experts in the field and offers an ideal reference guide for researchers and engineers in the fields of electrical/electronic engineering, control system and energy.
Soft Computing in Green and Renewable Energy Systems
Author: Kasthurirangan Gopalakrishnan
language: en
Publisher: Springer
Release Date: 2011-08-20
Soft Computing in Green and Renewable Energy Systems provides a practical introduction to the application of soft computing techniques and hybrid intelligent systems for designing, modeling, characterizing, optimizing, forecasting, and performance prediction of green and renewable energy systems. Research is proceeding at jet speed on renewable energy (energy derived from natural resources such as sunlight, wind, tides, rain, geothermal heat, biomass, hydrogen, etc.) as policy makers, researchers, economists, and world agencies have joined forces in finding alternative sustainable energy solutions to current critical environmental, economic, and social issues. The innovative models, environmentally benign processes, data analytics, etc. employed in renewable energy systems are computationally-intensive, non-linear and complex as well as involve a high degree of uncertainty. Soft computing technologies, such as fuzzy sets and systems, neural science and systems, evolutionary algorithms and genetic programming, and machine learning, are ideal in handling the noise, imprecision, and uncertainty in the data, and yet achieve robust, low-cost solutions. As a result, intelligent and soft computing paradigms are finding increasing applications in the study of renewable energy systems. Researchers, practitioners, undergraduate and graduate students engaged in the study of renewable energy systems will find this book very useful.
Wind and Solar Energy Systems
This book is designed to serve as a textbook for courses on renewable energy technology targetted at upper undergraduate or graduate students. This book can also be used as a core or supplementary text for courses in energy conservation and management and solar photo-voltaic design and application. This textbook covers the basic concepts of renewable energy resources, especially wind and solar energy. It contains 8 chapters covering all major renewable energy systems, resources, and related topics, as well as a brief introductory chapter on grid integration techniques in solar and wind energy systems. The book includes pedagogical features like examples and review questions and multiple choice questions to help the readers test their understanding. Reading lists, including web-based material, are included at the end of each chapter. The structure and pedagogy makes this book useful for self-study as well as for classroom use. The book can also be used as text for professional development courses for engineers employed in the energy industry.