Journal of Zhejiang University SCIENCE A
ISSN 1673-565X(Print), 1862-1775(Online), Monthly

2008   Vol. 9   No. 3   p. 401~409

Robust design and optimization for autonomous PV-wind hybrid power systems

Jun-hai SHI^†, Zhi-dan ZHONG, Xin-jian ZHU, Guang-yi CAO

(Institute of Fuel Cells, Shanghai Jiao Tong University, Shanghai 200240, China)
^†E-mail: shjh@sjtu.edu.cn
Received June 19, 2007; revision accepted Aug. 1, 2007; published online Dec. 8, 2007

Abstract: This study presents a robust design method for autonomous photovoltaic (PV)-wind hybrid power systems to obtain an optimum system configuration insensitive to design variable variations. This issue has been formulated as a constraint multi-objective optimization problem, which is solved by a multi-objective genetic algorithm, NSGA-II. Monte Carlo Simulation (MCS) method, combined with Latin Hypercube Sampling (LHS), is applied to evaluate the stochastic system performance. The potential of the proposed method has been demonstrated by a conceptual system design. A comparative study between the proposed robust method and the deterministic method presented in literature has been conducted. The results indicate that the proposed method can find a large mount of Pareto optimal system configurations with better compromising performance than the deterministic method. The trade-off information may be derived by a systematical comparison of these configurations. The proposed robust design method should be useful for hybrid power systems that require both optimality and robustness.

Key words: PV-wind power system,Robust design, Constraint multi-objective optimizations, Multi-objective genetic algorithms, Monte Carlo Simulation (MCS), Latin Hypercube Sampling (LHS)
doi:10.1631/jzus.A071317             CLC number: TB21; TK01

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