relation: https://khub.utp.edu.my/scholars/6569/
title: Application of Artificial Intelligence Methods for Hybrid Energy System Optimization
creator: Zahraee, S.M.
creator: Khalaji Assadi, M.
creator: Saidur, R.
description: Consciousness of the need to decrease our unnatural weather changes and of the critical increase in the costs of traditional sources of energy have motivated many nations to provide innovative energy strategies that promulgate renewable energy systems. For example, solar, wind and hydro related energies are renewable energy sources, and they are environmentally friendly with the potential for broad use. All of the load requirement conditions in comparison with single usage can provide more economical and dependable electricity, as well as environmentally friendly sources, by compounding such renewable energy sources using backup units to shape a hybrid scheme. Sizing the hybrid system elements optimally is one of the most important matters in this type of hybrid system, which could sufficiently meet all of the load demands with a minor financial investment. Although a number of studies have been performed on the optimization and sizing of hybrid renewable energy systems, this study presents a full analysis of Artificial Intelligence optimum plans in the literature, making the contribution of penetrating extensively the renewable energy aspects for improving the functioning of the systems economically. © 2016 Elsevier Ltd
publisher: Elsevier Ltd
date: 2016
type: Article
type: PeerReviewed
identifier:   Zahraee, S.M. and Khalaji Assadi, M. and Saidur, R.  (2016) Application of Artificial Intelligence Methods for Hybrid Energy System Optimization.  Renewable and Sustainable Energy Reviews, 66.  pp. 617-630.  ISSN 13640321     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84983732554&doi=10.1016%2fj.rser.2016.08.028&partnerID=40&md5=f12ff7d8df014878549553fb0c161146
relation: 10.1016/j.rser.2016.08.028
identifier: 10.1016/j.rser.2016.08.028