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|Title:||A survey on the application of artificial intelligence techniques for photovoltaic systems||Authors:||Mellit, Adel
Kalogirou, Soteris A.
|Keywords:||AI techniques;Artificial neural networks;Fuzzy logic;Genetic algorithm;Hybrid systems||Category:||Computer and Information Sciences||Field:||Natural Sciences||Issue Date:||12-Sep-2017||Publisher:||Elsevier Inc.||Source:||McEvoy's handbook of photovoltaics : fundamentals and applications, 2017, Pages 735-761||DOI:||https://doi.org/10.1016/B978-0-12-809921-6.00019-7||Abstract:||This chapter presents four of the major artificial intelligence (AI) techniques for photovoltaic applications: artificial neural networks (ANNs), fuzzy logic (FL), genetic algorithm (GA), and hybrid systems (HSs). The advantages of AI-based modeling and simulation techniques as alternatives to conventional physical modeling are explained.The text validates the premise that AI offers alternative ways to improve prediction accuracy and fault identification. The importance of digital hardware modules that can be integrated within systems is emphasized.Applications of AI techniques for modeling, control, sizing, prediction, and fault detection are described in some detail; conclusions are presented for each of the main AI techniques. References are provided for information on setup techniques.||URI:||http://ktisis.cut.ac.cy/handle/10488/12932||ISBN:||9780128103975||Rights:||© 2018 Elsevier Ltd||Type:||Book Chapter|
|Appears in Collections:||Κεφάλαια βιβλίων/Book chapters|
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