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Multi-Objective Optimization of Hybrid Renewable Energy System Using an Enhanced Multi-Objective Evolutionary Algorithm

Author

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  • Mengjun Ming

    (College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China)

  • Rui Wang

    (College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China)

  • Yabing Zha

    (College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China)

  • Tao Zhang

    (College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China)

Abstract

Due to the scarcity of conventional energy resources and the greenhouse effect, renewable energies have gained more attention. This paper proposes methods for multi-objective optimal design of hybrid renewable energy system (HRES) in both isolated-island and grid-connected modes. In each mode, the optimal design aims to find suitable configurations of photovoltaic (PV) panels, wind turbines, batteries and diesel generators in HRES such that the system cost and the fuel emission are minimized, and the system reliability/renewable ability (corresponding to different modes) is maximized. To effectively solve this multi-objective problem (MOP), the multi-objective evolutionary algorithm based on decomposition (MOEA/D) using localized penalty-based boundary intersection (LPBI) method is proposed. The algorithm denoted as MOEA/D-LPBI is demonstrated to outperform its competitors on the HRES model as well as a set of benchmarks. Moreover, it effectively obtains a good approximation of Pareto optimal HRES configurations. By further considering a decision maker’s preference, the most satisfied configuration of the HRES can be identified.

Suggested Citation

  • Mengjun Ming & Rui Wang & Yabing Zha & Tao Zhang, 2017. "Multi-Objective Optimization of Hybrid Renewable Energy System Using an Enhanced Multi-Objective Evolutionary Algorithm," Energies, MDPI, vol. 10(5), pages 1-15, May.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:5:p:674-:d:98310
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    References listed on IDEAS

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