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

• Published in: IET Chennai Fourth International Conference on Sustainable Energy and Intelligent Systems (SEISCON 2013) pp. 504 - 510
• Main Authors: Swamy, S.M, Rajakumar, B.R, Valarmathi, I.R
• Format: Conference Proceeding
• Language: English
• Published: Stevenage, UK IET 2013; The Institution of Engineering & Technology
• Subjects: Optimisation techniques; Power system management, operation and economics; Solar power stations and photovoltaic power systems; Wind power plants; cost reduction; opposition-based genetic algorithm; photovoltaic power systems; PV power generation; average annual load demand; genetic algorithms; power generation economics; hybrid wind-photovoltaic power system; OGA-CM; Cauchy mutation; wind power plants; optimal sizing; hybrid power systems
• ISBN: 9781785610301; 1785610309
• DOI: 10.1049/ic.2013.0361

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.