Optimal Sizing of Stand-alone PV System Using Grey Wolf optimization

Photovoltaic systems are among the leading renewable energy sources. Their main drawback is their high initial cost. Optimizing the size of the system is one of the possible options to minimise the cost. Sizing of the system is the proper selection of the rating and the number of the system components such as the solar panel, the battery, the charger, and the DC/AC inverter. In recent years, the artificial intelligence algorithms have been deployed in optimizing the size of renewable energy systems. In this paper, we optimize the size of stand-alone photovoltaic system by applying grey wolf optimization algorithm. The inputs to the algorithm are the load data, the solar radiation and the ambient temperature. The stand-alone photovoltaic system is modelled and implemented in Matlab. The life cycle cost of the system is selected as our objective function in the grey wolf optimization algorithm. Using different PV system components with different specifications and prices, the results of the grey wolf optimization algorithm sizing are optimum as proven by simulations.