| ABSTRACT:In optimal sizing of stand-alone hybrid wind/PV system, how to make more full use of wind and solar energy source, and how to configure PV modules, wind generators and batteries based on the load demand with higher reliability, lower system cost and lower lost of clean energy is a multi-objective optimization problem in nature.In this paper, weather modeling which is build at fist is one of the most important factors. Peak-Sun-Hours method is used to calculate solar radiation data, while the weibull distribution is used to simulate the wind speed. Monte Carlo method is used to simulate weather condition after considering the random condition. Then wind generators and PV Systems are modeling, LOLP and LOEP indices which reflect the reliability level and the lost of clean energy are proposed and calculated through Monte Carlo simulation.To solve the multi-objective optimization problem, a so called CSEA Multi-Objective Evolutionary Algorithm has been proposed in detail. Simulation results show that, The Chaotic Initial Generation helps to improve the initial diversity, the Grouping Selection Strategy and Self-adaptive Genetic Operator help to avoid pre-maturity and enhance the global searching ability of the algorithm. Comparisons with the single-objective optimization show that CSEA outperforms GA in terms of diversity preservation and in converging closer to the pareto-optimal frontier in one-run-time.Photovoltaic system and wind power system are compared with the hybrid wind/PV system in double-objective evolutionary algorithm. The result shows that stand-alone hybrid wind/PV system is more reasonable comparing with PV system or wind farm in power system.Application of CSEA on the Optimal Sizing of Stand-alone hybrid wind/PV system can improve system reliability, reduce the cost and energy waste, which has great significance.
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