A flower pollination optimization algorithm for an off-grid PV-Fuel cell hybrid renewable system

This research work crucially deals with a techno-economic feasibility study for off-grid solar photovoltaic fuel cell (PV/FC) hybrid systems. The hybrid renewable energy system is investigated for feeding electric to remote areas and isolated urban regions in Egypt. To achieve this goal, all the system equipment are modeled, simulated and the area under study data is gathered. The objective function is formulated depending on the total annual cost (TAC). The Flower Pollination Algorithm (FPA), as an efficient recent metaheuristic optimization method, proposed to estimate the optimum number of both PV panels and the FC/electrolyzer/H 2 storage tanks set mandatory where the least total net present value (TNPV) is reached. The loss of power supply probability (LPSP) is considered to enhance the performance of the proposed design. The effect of the variation of FC, electrolyzer, H 2 storage tanks and the PV power system initial cost on the levelized cost of energy (LCOE) is presented through a comprehensive sensitivity analysis. Through Matlab™ program, the numerical simulation results obtained by the FPA algorithm have been compared to the corresponding outcomes while using the artificial bee colony (ABC) and the Particle Swarm Optimization (PSO) techniques. According to the simulation outcomes analysis, the FPA Algorithm has the less fulfillment time and good rendering between the other algorithms. In addition, the optimum system configuration is acquired using FPA with the optimal hybridization of 27 solar PV, 28 FCs, 58 electrolyzers and 37 H 2 storage tanks for an LPSP and PEE of 1.52% and 4.68% respectively. The system TNPV is $3,244,897 with the LCOE of 0.334 $/kWh.