Applications of fuzzy logic in renewable energy systems – A reviewL. Suganthi, S. Iniyan and Anand A. Samuel Renewable and Sustainable Energy Reviews, 2015, vol. 48, issue C, 585-607 Abstract: 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. Keywords: Fuzzy logic; Neuro-fuzzy; ANFIS; Fuzzy AHP; Fuzzy MCDM (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:rensus:v:48:y:2015:i:c:p:585-607 Ordering information: This journal article can be ordered from DOI: 10.1016/j.rser.2015.04.037 Access Statistics for this article Renewable and Sustainable Energy Reviews is currently edited by L. Kazmerski More articles in Renewable and Sustainable Energy Reviews from Elsevier |
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