Optimal Economical Sizing Of A PV-Wind Hybrid Energy System Using Genetic Algorithm

In this paper, a new formulation for optimizing the design of a photovoltaic (PV)-wind hybrid energy home system, incorporating a storage battery, is developed. This formulation is carried out with the purpose of arriving at a selection of the system economical components that can reliably satisfy the load demand. Genetic algorithm (GA) optimization technique is utilized to satisfy two purposes. The first is to minimize the formulated objective function, which is the total cost of the proposed hybrid system. Whereas, the second is to ensure that the load is served according to certain reliability criteria, by maintaining the loss of power supply probability (LPSP) of the system lower than a certain predetermined value. Two computer programs are designed, using MATLAB code in a two M-files, to simulate the proposed hybrid system and to formulate the optimization problem by computing the coefficients of the objective function and the constraints. Also, these two programs are utilized together with the GA tool under MATLAB software to yield the optimum PV, wind, and battery ratings. The results verified that PV-wind hybrid systems feature lower system cost compared to the cases where either PV-alone or wind-alone systems are used.