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

Mengjun Ming, Rui Wang, Yabing Zha and Tao Zhang
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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

Energies, 2017, vol. 10, issue 5, 1-15

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.

Keywords: hybrid renewable energy system (HRES); power grid; multi-objective optimization; multi-objective evolutionary algorithm (MOEA); penalty-based boundary intersection method (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (22)

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