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

作     者：Jun-hai SHI Zhi-dan ZHONG Xin-jian ZHU Guang-yi CAO 

作者机构：Institute of Fuel Cells Shanghai Jiao Tong University Shanghai 200240 China 

出 版 物：《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》 (浙江大学学报（英文版）A辑（应用物理与工程）)

年 卷 期：2008年第9卷第3期

页      面：401-409页

核心收录：

学科分类：080702[工学-热能工程] 08[工学] 0807[工学-动力工程及工程热物理] 

主　　题：PV-wind power system Robust design Constraint multi-objective optimizations Multi-objective genetic algorithms Monte Carlo Simulation (MCS) Latin Hypercube Sampling (LHS) 

摘      要：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.