eprintid: 6569
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/65/69
datestamp: 2023-11-09 16:18:21
lastmod: 2023-11-09 16:18:21
status_changed: 2023-11-09 16:07:05
type: article
metadata_visibility: show
creators_name: Zahraee, S.M.
creators_name: Khalaji Assadi, M.
creators_name: Saidur, R.
title: Application of Artificial Intelligence Methods for Hybrid Energy System Optimization
ispublished: pub
keywords: Artificial intelligence; Investments; Natural resources; Renewable energy resources, Artificial intelligence methods; Energy strategy; Energy system optimizations; Energy systems; Hybrid energy system; Optimisations; Renewable energies; Renewable energy source; Sources of energy; Weather change, Hybrid systems
note: cited By 185
abstract: 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
date: 2016
publisher: Elsevier Ltd
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84983732554&doi=10.1016%2fj.rser.2016.08.028&partnerID=40&md5=f12ff7d8df014878549553fb0c161146
id_number: 10.1016/j.rser.2016.08.028
full_text_status: none
publication: Renewable and Sustainable Energy Reviews
volume: 66
pagerange: 617-630
refereed: TRUE
issn: 13640321
citation:   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