Optimization of hybrid renewable energy power systems: A review View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-01

AUTHORS

Binayak Bhandari, Kyung-Tae Lee, Gil-Yong Lee, Young-Man Cho, Sung-Hoon Ahn

ABSTRACT

The characteristics of power produced from photovoltaic (PV) and Wind systems are based on the weather condition. Both the system are very unreliable in itself without sufficient capacity storage devices like batteries or back-up system like conventional engine generators. The reliability of the system significantly increases when two systems are hybridized with the provision of storage device. Even in such case, sufficient battery bank capacity is required to provide power to the load in extended cloudy days and non-windy days. Therefore the optimal sizing of system component represents the important part of hybrid power system. This paper summarizes recent trends of energy usage from renewable sources. It discusses physical modeling of renewable energy systems, several methodologies and criteria for optimization of the Hybrid Renewable Energy System (HRES). HRES is getting popular in the present scenario of energy and environmental crises. In this paper, we present a comprehensive review on the current state of optimization techniques specifically suited for the small and isolated power system based on the published literatures. The recent trend in optimization in the field of hybrid renewable energy system shows that artificial intelligence may provide good optimization of system without extensive long term weather data. More... »

PAGES

99-112

References to SciGraph publications

  • 2014-04. Mathematical modeling of hybrid renewable energy system: A review on small hydro-solar-wind power generation in INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING-GREEN TECHNOLOGY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s40684-015-0013-z

    DOI

    http://dx.doi.org/10.1007/s40684-015-0013-z

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1020993110


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