Metaheuristic Algorithm to Find Optimal Sizing of Stand-Alone Hybrid Energy System in Remote Areas: A review

Abstract

In remote areas, electricity is provided by diesel generators, which have many disadvantages, such as their dependence entirely on fossil fuels that cause global warming due to emissions of harmful gases such as carbon dioxide, and the high maintenance cost of these generators, as well as the difficulty of transporting fossil fuels to them. Therefore, the world has tended to use renewable energy sources, due to their advantages such as their presence in all regions of the world, they do not emit harmful gases and their long life. However, renewable energy sources also have disadvantages such as high investment cost, and their intermittent nature because they depend on climate data. Therefore, the optimal sizing of these sources is considered an important factor to increase reliability, reduce emissions, reduce costs, and other goals. These problems can be solved by modern techniques, a metaheuristic algorithm that is more famous than traditional algorithms because it has good results and faster processing time. In this paper, we present a comprehensive review for used metaheuristic algorithms to find the optimal sizing of the energies used in the hybrid energy system (HES) for single and multi-objective optimization. Also, we review the main combinations of HES including their assessment parameters of economics, environmental, and reliability.