Economic analysis and design of stand-alone wind/photovoltaic hybrid energy system using Genetic algorithm
A well-designed and optimized hybrid energy system can be cost effective, has a high reliability and can improve the quality of life in remote rural areas. Hybrid system can be able to adapt to climate changes. In this study, Genetic Algorithm (GA) is developed for the prediction of the optimal sizing coefficient of wind/PV hybrid energy system in remote areas. The objective function for cost is constructed, which includes initial costs, yearly operating costs and maintenance costs. The hybrid system consists of photovoltaic panels, wind turbines, Diesel Generator and storage batteries. Due to the complexity of nonlinear integral planning in hybrid energy systems, Genetic algorithm is used to solve this problem. By use of Genetic algorithm operation strategy, the global optimal searching ability of the proposed algorithm is further improved. The improved Genetic algorithm can avoid to the local minimum trap. The developed GA Algorithm has been applied to design the wind/ PV hybrid energy systems to supply a varying load located in the area of Jaipur, Rajasthan (India). The optimal solution is achieved using proposed GA method and shows that the system can deliver energy in a stand-alone installation with an acceptable cost.