Abstract
In recent years, design optimization of hybrid power generation systems which utilize renewable energy resources has received a significant attention. One of the most challenging problems in design of such systems is optimal sizing. To tackle this drawback, this paper presents an efficient and robust optimization approach for size optimization of a hybrid system composed of photovoltaic (PV) panel, diesel generator and fuel cell (FC). The proposed method is a modified version of crow search algorithm (CSA) in which awareness probability is adjusted by an adaptive manner. In the sizing framework, total net present cost (TNPC) is minimized subject to two main constraints: loss of power supply probability (LPSP) and renewable energy portion (REP). Simulation results show that (1) REP has a considerable impact on TNPC of the designed system, (2) optimal combination of PV, diesel generator, FC, electrolyzer and hydrogen tank leads to establishing a reliable and cost-effective hybrid power generation system and (3) the proposed method (CSAadaptive-AP) finds more promising and robust results than original CSA, genetic algorithm (GA) and particle swarm optimization (PSO).
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