Stand-alone hybrid renewable energy system simulation and optimization using imperialist competitive algorithm

Owing to limited capacity of fossil fuel resources, renewable sources of energy such as solar and wind are attracting interests as an alternative. Meanwhile, hybrid systems suggest better reliability and efficiency due to variety in weather condition. In this paper an optimum design of a stand-alone hybrid PV-wind-battery is represented using Imperialist Competitive Algorithm (ICA). The final goal of the paper is minimization the proposed system total cost during the project lifetime by considering supplying the load. For this purpose, cost function of PV, wind and battery are derived by deliberating local power demand, solar radiation, wind speed and site temperature data. After that the total cost of the system is optimized by Particle Swarm Optimization (PSO) and ICA A comparison between the two methods is provided and benefits of ICA are highlighted. Finally, the effect of changing optimization´s parameter is debated.