Designing framework of hybrid photovoltaic-biowaste energy system with hydrogen storage considering economic and technical indices using whale optimization algorithm

Abstract In this study economic, reliable and environmentally friendly designing of a hybrid photovoltaic-biowaste-fuel cell (PV-Biowaste-FC) system based on hydrogen storage energy is presented using whale optimization algorithm (WOA) considering the availability of components for 20 years useful lifespan of the project. The WOA is a robust meta-heuristic method for solving optimization problems with high convergence speed and accuracy. The fuel cell system includes an electrolyzer, a hydrogen storage tank, and a fuel cell stack. The objective function is defined as minimization of total net present cost (TNPC) include investment, maintenance and repair and replacement cost and reliability constraint is considered as loss of power supply probability (LPSP). The optimization variables include the area occupied by photovoltaic (PV) panels, number of biowaste units, electrolyzers, hydrogen storage tanks, fuel cells, and inverters that are optimally determined by the WOA considering the TNPC and LPSP. To validate the WOA method in the PV-Biowaste-FC designing, its performance is compared with the particle swarm optimization (PSO) method. Simulations have been carried out for different scenarios including designing of Biowaste-FC and PV-Biowaste-FC system, evaluating the effect of PV, Biowaste and inverter availability and also effect of investment cost of FC on the system designing. Simulation results show that the hybrid system with the participation of all resources and hydrogen storage system as the PV-Biowaste-FC presents the minimum TNPC (2.820 M$) and the lower LPSP (0.0029) compared to the other combinations. Also, the cost of energy (COE) value for the hybrid PV-Biowaste-FC system is obtained at 0.5238 $/kWh. The proposed method for designing the hybrid system provides better performance than the PSO in achieving less TNPC and better reliability with higher convergence speed and accuracy. Further, the effects of the availability of PV units, biowaste, and inverter on the system designing are evaluated. According to the results, decreasing the availability of the components increases the TNPC and weakens the reliability indices.