Abstract
With the rapid development of the use of renewable energy systems, it is becoming more and more important to combine different sources into hybrid renewable energy systems. Many parameters in hybrid renewable energy systems must be optimized to effectively size hybrid system components to achieve economic, technical, and design goals practically. This paper focuses on the optimal configuration of off-grid hybrid renewable energy systems (HRES). The system consists of a photovoltaic (PV), wind turbine (WT) and battery bank (BB), fuel cell (FC) with hydrogen tank (H2-tank), and electrolyzer (Elect). The optimal size of the proposed HRES component is achieved using a novel meta-heuristic technique called the whale optimization algorithm (WOA). WOA improves the optimal configuration of HRES to produce the best minimum value of the fitness function, which converges to the global optimal solution after several iterations. The proposed WOA is used to solve the multi-objective optimization problem of the cost of energy (COE) in $/kWh and the total net present cost (TNPC) in $. Two recent algorithms, particle swarm optimization (PSO) and gray wolf optimizer (GWO), have also been implemented in this work to demonstrate the effectiveness of the proposed algorithm.
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