LAPSE:2021.0584
Published Article
LAPSE:2021.0584
Optimal Sizing of an Island Hybrid Microgrid Based on Improved Multi-Objective Grey Wolf Optimizer
Wenqiang Zhu, Jiang Guo, Guo Zhao, Bing Zeng
June 29, 2021
The hybrid renewable energy system is a promising and significant technology for clean and sustainable island power supply. Among the abundant ocean energy sources, tidal current energy appears to be very valuable due to its excellent predictability and stability, particularly compared with the intermittent wind and solar energy. In this paper, an island hybrid energy microgrid composed of photovoltaic, wind, tidal current, battery and diesel is constructed according to the actual energy sources. A sizing optimization method based on improved multi-objective grey wolf optimizer (IMOGWO) is presented to optimize the hybrid energy system. The proposed method is applied to determine the optimal system size, which is a multi-objective problem including the minimization of annualized cost of system (CACS) and deficiency of power supply probability (DPSP). MATLAB software is utilized to program and simulate the hybrid energy system. Optimization results confirm that IMOGWO is feasible to optimally size the system, and the energy management strategy effectively matches the requirements of system operation. Furthermore, comparison of hybrid systems with and without tidal current turbines is undertaken to confirm that the utilization of tidal current turbines can contribute to enhancing system reliability and reducing system investment, especially in areas with abundant tidal energy sources.
Keywords
energy management, grey wolf optimizer, hybrid energy system, island microgrid, sizing optimization, tidal current energy
Suggested Citation
Zhu W, Guo J, Zhao G, Zeng B. Optimal Sizing of an Island Hybrid Microgrid Based on Improved Multi-Objective Grey Wolf Optimizer. (2021). LAPSE:2021.0584
Author Affiliations
Zhu W: School of Power and Mechanical Engineering, Wuhan University, Wuhan 430072, China; Intelligent Power Equipment Technology Research Center, Wuhan University, Wuhan 430072, China
Guo J: School of Power and Mechanical Engineering, Wuhan University, Wuhan 430072, China; Intelligent Power Equipment Technology Research Center, Wuhan University, Wuhan 430072, China
Zhao G: Hubei University of Technology, Wuhan 430068, China
Zeng B: School of Mechanical and Electrical Engineering, Nanchang Institute of Technology, Nanchang 330029, China [ORCID]
Journal Name
Processes
Volume
8
Issue
12
Article Number
E1581
Year
2020
Publication Date
2020-11-30
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr8121581, Publication Type: Journal Article
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LAPSE:2021.0584
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doi:10.3390/pr8121581
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Jun 29, 2021
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Jun 29, 2021
 
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Calvin Tsay
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