Optimal and Intelligent Designing of Stand-alone Hybrid Photovoltaic/Wind/Fuel Cell System Considering Cost and Deficit Load Demand Probability, Case Study for Iran (Bushehr City)

This paper presents the optimal and intelligent design of photovoltaic-wind-hydrogen system with the aim of minimizing the overall cost of the system and considering the reliability constraints based on annual radiation and wind speed data in Bushehr city. The hydrogen storage system includes an electrolyzer, a hydrogen storage tank and a fuel cell. Overall costs of hybrid systems include initial investment costs, maintenance and operation and replacement of components, and reliability constraint indicate deficit load demand probability (DLDP). In this study, the decision variables were optimized system capacity including number of solar panels, wind turbine, electrolyzer power capacity, mass of hydrogen storage tank, fuel cell capacity and power transfered with inverter by Grey Wolf Optimization (GWO) algorithm that has high convergence speed and accuracy. System design is presented in different scenarios of hybrid system combinations. To verify the proposed method, the results are compared with the results of Particle Swarm Optimization (PSO) algorithm. The simulation results show that the GWO method performs better in design of optimization with lower overall cost and better DLDP than the PSO in different combinations. The results show that photovoltaic -hydrogen storage due to the low wind speed potential in Bushehr city is the optimal combination based on cost and reliability for load supply based on renewable resources hybrid systems. In addition, the results show that the use of higher efficiency inverters reduces energy production costs and improves load reliability. In addition, the results indicate that the outage of renewable units in the design problem has a significant effect on system cost and reliability.