Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/12932
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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