Artificial intelligence techniques for photovoltaic applications: A review

By Adel Mellit, Soteris A. Kalogirou. 2008

951 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/f86b88e3eb0df51c9846512094b7562891c903ba

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In Artificial Intelligence

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Citations in the corpus

Forecasting of preprocessed daily solar radiation time series using neural networks (2010, methodology): “In this way, we have investigated both in time series forecasting, which is a challenge in many fields, and in artificial intelligence techniques, which are becoming more and more popular in the renewable energy domain (Mellit and Kalogirou, 2008; Mellit et al., 2009) and particularly for the predic”
An Overview of Artificial Intelligence Applications for Power Electronics (2020, methodology): “However, it only includes a very limited AI-based fault detection method.”
Day-Ahead Photovoltaic Forecasting: A Comparison of the Most Effective Techniques (2019, methodology): “In both cases, the original data have been pre-processed as follows [53]:”
Use of support vector regression and numerically predicted cloudiness to forecast power output of a photovoltaic power plant in Kitakyushu, Japan (2012, methodology): “Artificial intelligence models have been used in PV applications [5].”
Global Research on Artificial Intelligence from 1990-2014: Spatially-Explicit Bibliometric Analysis (2016, background): “…and other fields working on similar problems, and a new commitment by researchers to solid mathematical methods and rigorous scientific standards [6,7]. and other ﬁelds working on similar problems, and a new commitment by researchers to solid mathematical Today, AI and its applications play an…”
Parameter extraction of solar cell models using repaired adaptive differential evolution (2013, background): “Therefore, in the later approach es, the use of artificial intelligence techniques for solar cell parameter extraction has received considerable attention recently [15, 16], such as genetic algorithms (GAs) [12, 17], p article swarm optimization (PSO) [18, 19, 20, 21, 22], differential evolution (DE”
Applications of artificial neural networks for thermal analysis of heat exchangers – A review (2015, background): “Similarly, many researchers had reviewed the applications of ANN for refrigeration, air conditioning and heat pump systems [12], heat transfer problems in nuclear engineering [13], sizing of solar photovoltaic systems [14], modeling and control of combustion processes [15], modeling of energy system”
Sustainable energy systems: Role of optimization modeling techniques in power generation and supply—A review (2011, methodology): “Mellita and Kalogirou [146] used AI techniques to olve problems in photovoltaic systems application including fore18 7336 7972 3.”