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CLC number: TB21; TK01

On-line Access: 2007-12-08

Received: 2007-06-19

Revision Accepted: 2007-08-01

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Journal of Zhejiang University SCIENCE A 2008 Vol.9 No.3 P.401~409

http://doi.org/10.1631/jzus.A071317


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


Author(s):  Jun-hai SHI, Zhi-dan ZHONG, Xin-jian ZHU, Guang-yi CAO

Affiliation(s):  Institute of Fuel Cells, Shanghai Jiao Tong University, Shanghai 200240, China

Corresponding email(s):   shjh@sjtu.edu.cn

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


Jun-hai SHI, Zhi-dan ZHONG, Xin-jian ZHU, Guang-yi CAO. Robust design and optimization for autonomous PV-wind hybrid power systems[J]. Journal of Zhejiang University Science A, 2008, 9(3): 401~409.

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author="Jun-hai SHI, Zhi-dan ZHONG, Xin-jian ZHU, Guang-yi CAO",
journal="Journal of Zhejiang University Science A",
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pages="401~409",
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publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A071317"
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%A Jun-hai SHI
%A Zhi-dan ZHONG
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%A Guang-yi CAO
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%DOI 10.1631/jzus.A071317

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T1 - Robust design and optimization for autonomous PV-wind hybrid power systems
A1 - Jun-hai SHI
A1 - Zhi-dan ZHONG
A1 - Xin-jian ZHU
A1 - Guang-yi CAO
J0 - Journal of Zhejiang University Science A
VL - 9
IS - 3
SP - 401
EP - 409
%@ 1673-565X
Y1 - 2008
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.A071317


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.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

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