Document Type : Original Article
Science Explorer Group, London, United Kingdom
Renewable energy technology is quickly developing in last decades due to the increasing attention of countries to sustainable and clean energy, and is constantly evolving in terms of technology. Nevertheless, there are obstacles to this case, such as rising costs and declining reliability due to the volatility of renewable power resources. Renewable technologies with the aim of using one source to cover other weaknesses, is one way to overcome these obstacles. In the present paper, a technique for optimum sizing of the components in a hybrid renewable power system (HRPS) consists of PV panels, electrolyzer, fuel cell, wind turbines, and the converters has been studied with keeping the value of the Net Present Cost (NPC) minimum. For giving a more efficient power generation cost, the optimization is obtained by using an Adaptive version of Wildebeest Herd Optimizer (AWHO). The main profit of the suggested algorithm is to resolve the main disadvantages of the other metaheuristic from the literature, like reliability, convergence speed, premature convergence, and accuracy, as it is possible. The proposed system is performed to a real-world case study in Yantai, China. Simulation results are put in comparison with several latest methods.
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