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 and lower system cost is a multi-objective optimization problem in nature. In this paper, the wind generators and PV Systems are modeling at first. Loss of load probability (LOLP) and loss of energy probability (LOEP) indices which reflect the reliability level and the lost of energy are proposed and calculated through Monte Carlo simulation. To solve the multi-objective optimization problem, a so called chaos self-adaptive evolutionary algorithm (CSEA) multi-objective evolutionary algorithm is 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. Comparison 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. 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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2011, Vol. 26 
