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Capacity optimization allocation of hybrid energy storage system based on improved NSGA-II algorithm
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Xin LI, Yali ZHANG, Song LI, Ya QIU, Kun QIU
Thermal Power Generation | 2024, 53(12) : 49 - 56
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Thermal Power Generation | 2024, 53(12): 49-56
• Special topic of low-carbon power technology •
Capacity optimization allocation of hybrid energy storage system based on improved NSGA-II algorithm
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Xin LI, Yali ZHANG, Song LI, Ya QIU, Kun QIU
Affiliations
  • School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China
Published: 2024-12-25 doi: 10.19666/j.rlfd.202405113
Outline
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Against the shortcomings of intermittency and instability of photovoltaic power generation in microgrids, a hybrid energy storage system composed of vanadium redox batteries (VRB) and super capacitors (SC) is utilized to smooth out the power fluctuations in standalone microgrids, thus to improve the power supply reliability of standalone microgrids. Considering the capacity allocation problem of the hybrid energy storage system, a multi-objective hybrid energy storage system capacity optimization model that minimizes the average annual cost of the hybrid energy storage system and the load shortage rate is developed. Aiming at the poor local search ability of the conventional elite non-dominated solution sorting genetic algorithm (NSGA-II) algorithm for solving the multi-objective optimization problem, an NSGA-II algorithm based on the improved elite retention strategy is proposed. By introducing a new fitness function, the algorithm is sorted and reasonably retains the elite individuals, so it improves the optimization effect, thus to enhance the local search ability, continuously approach the Pareto true frontier, and obtain better capacity configuration solutions. Finally, the rationality of the proposed method is verified by arithmetic examples.

stand-alone microgrids  /  hybrid energy storage  /  capacity optimized allocation  /  improved NSGA-II
Xin LI, Yali ZHANG, Song LI, Ya QIU, Kun QIU. Capacity optimization allocation of hybrid energy storage system based on improved NSGA-II algorithm[J]. Thermal Power Generation, 2024 , 53 (12) : 49 -56 . DOI: 10.19666/j.rlfd.202405113
Funding
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  • National Natural Science Foundation of China(62202138)
Appendix
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Year 2024 volume 53 Issue 12
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98
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Article Info
doi: 10.19666/j.rlfd.202405113
  • Receive Date：2024-05-31
  • Online Date：2026-03-06
  • Published：2024-12-25
Article Data
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  • Received：2024-05-31
Funding
National Natural Science Foundation of China(62202138)
Affiliations
    School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China
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https://castjournals.cast.org.cn/joweb/rlfd/EN/10.19666/j.rlfd.202405113
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