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Applications of fuzzy logic in renewable energy systems - A review

Journal

RENEWABLE & SUSTAINABLE ENERGY REVIEWS
Volume 48, Issue -, Pages 585-607

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rser.2015.04.037

Keywords

Fuzzy logic; Neuro-fuzzy; ANFIS; Fuzzy AHP; Fuzzy MCDM

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In recent years, with the advent of globalization, the world is witnessing a steep rise in its energy consumption. The world is transforming itself into an industrial and knowledge society from an agricultural one which in turn makes the growth, energy intensive resulting in emissions. Energy modeling and energy planning is vital for the future economic prosperity and environmental security. Soft computing techniques such as fuzzy logic, neural networks, genetic algorithms are being adopted in energy modeling to precisely map the energy systems. In this paper, an attempt has been made to review the applications of fuzzy logic based models in renewable energy systems namely solar, wind, bio-energy, micro-grid and hybrid applications. It is found that fuzzy based models are extensively used in recent years for site assessment, for installing of photovoltaic/wind farms, power point tracking in solar photovoltaic/wind, optimization among conflicting criteria. The review indicates that fuzzy based models provide realistic estimates. (C) 2015 Elsevier Ltd. All rights reserved.

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