An overview of optimization techniques used for sizing of hybrid renewable energy systems

Variability of renewables like solar and wind remains a major concern, despite a substantial decrease in the capital cost of their power conversion devices. One of the methods to improve the reliability of power is to combine more than one renewable power sources and storage systems together, as per the local renewable potential, is called a hybrid renewable energy system (HRES). The exact sizing of individual sources and storage systems to fulfill the respective load demand for the renewable potential of the site is not a straightforward task. Different sizing and optimization methodologies are developed by the research community. A comprehensive overview of the literature of these methodologies is carried out in this paper. Classical techniques were being applied to the HRES sizing, but their limitations led researchers to increasingly look for multi-objective heuristic techniques. This has led to a range of evolutionary algorithms being employed lately. The robustness of these techniques made them an effective tool for the search of global optimum, but their convergence speed may well be slower in comparison to gradient-based methods in the vicinity of the optimum point. It is needed to come up with novel hybrid techniques, which can carefully combine the conventional and evolutionary techniques by augmenting their advantages and at the same time avoiding their shortcomings. The literature survey proves that HRES from very small capacity of a few watts to many megawatts have been proposed for a variety of different locations throughout the world with varying degrees of cost of energy.