Optimally-sized design of a wind/photovoltaic/fuel cell hybrid system based on grey wolf optimization algorithm (GWO)

This study developed a hybrid system composed of wind turbines, PV cells, and fuel cells to supply a specific (deterministic) load model. The purpose of this design was to minimize the cost of energy generation over a period of 20-year while satisfying a set of system reliability constraints. In this paper, the data pertaining to load demand, sunlight and wind speed were considered to be known and deterministic. This design considered the failure of three main system components, namely, wind turbines, PV cells and AC/DC converter, and incorporated a number of cost factors such as initial investment, operating and maintenance expenses, and value of lost load (VoLL). The wind and solar data used in this study pertained to northwestern regions of Iran. This paper used gray wolf optimization algorithm (GWO) to optimize the system and compared the results with the results of particle swarm PSO. The stated objective of this paper was to determine the optimal value of system components, i.e. the number of wind turbines, the number and angle of PV arrays, and the size of electrolyzer, hydrogen tanks, fuel cells, and DC/AC converters. The costs incorporated into this design included net present value (NPV) of investment, costs of equipment, replacement and maintenance, and the costs arising from power supply interruption (VoLL), all for a period of 20 years considered as the system lifetime. Keywords: Grey-wolf Optimization algorithm, Hybrid Systems, Renewable energies