Sizing methods and optimization techniques for PV-wind based hybrid renewable energy system: A review. (October 2018) - Anoune, Kamal; Bouya, Mohsine; Astito, Abdelali; Abdellah, Abdellatif Ben
Abstract: Solar and wind energy are considered as promising electrical generating sources. These renewable energies are omnipresent, with free access, and a friendly environmental impact. Their integration remains technically and economically advantageous for electrical generation in isolated areas (IS). In several cases, the separate use of solar and wind energy sources may result in considerable over-sizing, which makes the single renewable energy sources in implementation very costly. It is found that the use of one of the optimization sizing techniques could help to guarantee the maximum power reliability and the minimum system cost for the future hybrid implementation. Moreover, a remarkable interest is manifesting for the use of solar and wind renewable energy sources (RES), which provide a realistic form of electrical generation in isolated areas. This paper provides an updated literature review, of the most applied method and techniques used in sizing and optimization of PV-Wind based hybrid system (PWHS) for an isolated area aiming to reach the best compromise between power reliability and hybrid system costs. Furthermore, this work discusses a comparison of the most common topologies used for the implementation of PWHS, then, presents a mathematical model of the hybrid system components with an emphasis on the importance of power reliability and system cost, Finally, provides an extensive analysis of software tools and algorithm approach used in sizing optimization. Highlights: Comparison of the most common implementation topologies of PWHS is presented. Presentation of different parameter of power reliability and system cost. Stochastic and deterministic methodology for sizing a PWHS. Extensive analysis of the software tools used in sizing optimization is done. Classifying the sizing optimization techniques using an algorithm approach.