@article{scholars6569,
             doi = {10.1016/j.rser.2016.08.028},
            note = {cited By 185},
          volume = {66},
           title = {Application of Artificial Intelligence Methods for Hybrid Energy System Optimization},
            year = {2016},
           pages = {617--630},
       publisher = {Elsevier Ltd},
         journal = {Renewable and Sustainable Energy Reviews},
          author = {Zahraee, S. M. and Khalaji Assadi, M. and Saidur, R.},
            issn = {13640321},
             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},
        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},
        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. {\^A}{\copyright} 2016 Elsevier Ltd}
}