Design of hybrid wind and photovoltaic power system using opposition-based genetic algorithm with Cauchy mutation

In recent decades, depletion of fossil fuels and its demand emerge as renewable energy in the field of power generation. Amid eco-friendly based renewable energy, wind and photovoltaic play a vital role in power generation. Nonetheless, this form of power generation needs more advancement to retrieve optimal power flow under economical conditions. This paper aims to predict optimal sizing for hybrid wind and photovoltaic (PV) power generation under minimized cost. This optimal sizing of hybrid Wind-PV is accomplished by satisfying the average annual load demand. This process happens via opposition based genetic algorithm with Cauchy mutation (OGA-CM) and the proposed OGA-CM performance measure is compared with Opposition based Genetic Algorithm and Genetic Algorithm. The result shows that our proposed OGA-GA produces superior result than those of the other two. The overall computation process is done in the working platform of MATLAB R2013.