Suman Lata (Hrsg.) Tripathi
Introduction to AI Techniques for Renewable Energy System
Ebook (EPUB Format)
This book helps the undergraduate, graduate students and Academician to learn the concept of Artificial Intelligence techniques used in renewal energy with suitable real-life examples. Artificial intelligence (AI) techniques play an essential role in modeling, analysis, and prediction of the performance and control of renewable energy. The algorithms used to model, control, or predict performances of the energy systems are complicated involving differential equations, enormous computing power, and time requirements. Instead of complex rules and mathematical routines, AI techniques can learn critical information patterns within a multidimensio…
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Beschreibung
This book helps the undergraduate, graduate students and Academician to learn the concept of Artificial Intelligence techniques used in renewal energy with suitable real-life examples. Artificial intelligence (AI) techniques play an essential role in modeling, analysis, and prediction of the performance and control of renewable energy. The algorithms used to model, control, or predict performances of the energy systems are complicated involving differential equations, enormous computing power, and time requirements. Instead of complex rules and mathematical routines, AI techniques can learn critical information patterns within a multidimensional information domain. Design, control, and operation of renewable energy systems require a long-term series of meteorological data such as solar radiation, temperature, or wind data. Such long-term measurements are often non-existent for most of the interest locations or, wherever they are available, they suffer from several shortcomings (e.g. inferior quality of data, in-sufficient long series, etc.). For overcoming these problems, AI techniques appear to be one of the most substantial parts of the book. The book summarizes commonly used AI methodologies in renewal energy, with a particular emphasis on neural networks, fuzzy logic, and genetic algorithms. Book outlines selected AI applications for renewable energy. In particular, discusses methods using the AI approach for the following applications using suitable examples: prediction and modeling of solar radiation, seizing, performances, and controls of the solar photovoltaic (PV) systems.Key selling Features:The impact of the proposed book is to provide a significant area of concern to develop a foundation for the implementation process renewable energy system with intelligent techniques.The researchers working on a renewable energy system can correlate their work with intelligent and machine learning approaches.To make aware of the international standards for intelligent renewable energy systems design, reliability and maintenance.To give better incites of the solar cell, biofuels, wind and other renewable energy system design and characterization, including the equipment for smart energy systems.
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V215:
Noch nicht erschienen, Juni 2021
Produktdetails
Weitere Autoren: Dubey, Mithilesh Kumar (Hrsg.) / Rishiwal, Vinay (Hrsg.) / Padmanaban, Sanjeevi Kumar (Hrsg.)
- ISBN: 978-1-00-039248-7
- EAN: 9781000392487
- Produktnummer: 35451257
- Verlag: Taylor & Francis Ltd.
- Sprache: Englisch
- Erscheinungsjahr: 2021
- Seitenangabe: 448 S.
- Plattform: EPUB
- Abbildungen: 196 schwarz-weiße Abbildungen, 21 schwarz-weiße Fotos, 175 schwarz-weiße Zeichnungen, 43 schwarz-weiße Tabellen
Über den Autor
Suman Lata Tripathi is working as a Professor at School of Electronics and Electrical Engineering, Lovely Professional University, India. Mithilesh Kumar Dubey is working as an Associate Professor at School of Computer Science and Engineering, Lovely Professional University, India. Vinay Rishiwal is working as a Professor at Department of Computer Science and Information Technology, Faculty of Engineering and Technology, MJP Rohilkhand University, Bareilly, Uttar Pradesh, India. Sanjeevikumar Padmanaban is working as a faculty member, at Department of Energy Technology, Aalborg University, Esbjerg, Denmark.
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