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Photovoltaic Array Power Tracking Strategy with Improved Levy-flight Grey Wolf Optimization and Variable-step Perturbation & Observation
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Baohong LIU, Bin CHEN, Lifeng QIAN, Yinuo SHI, Li LÜ
Journal of Power Supply | 2026, 24(4) : 110 - 121
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Journal of Power Supply | 2026, 24(4): 110-121
• Renewable Energy Generation and Energy Storage •
Photovoltaic Array Power Tracking Strategy with Improved Levy-flight Grey Wolf Optimization and Variable-step Perturbation & Observation
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Baohong LIU, Bin CHEN, Lifeng QIAN, Yinuo SHI, Li LÜ
Affiliations
  • School of Information Engineering, Jiangxi University of Water Resources and Electric Power, Nanchang 330099, China
Published: 2026-04-30 doi: 10.13234/j.issn.2095-2805.2026.4.110
Outline
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Aimed at the problems of slow maximum power point tracking (MPPT) convergence speed, low searching accuracy and susceptibility to falling into local optimum in the traditional grey wolf optimization (GWO) algorithm caused by multi-peak output power of photovoltaic (PV) arrays under partial shadow conditions, an algorithm with an improved Levy-flight GWO and variable-step perturbation & observation (ILGWO-VP&O) method is proposed. During the global searching, a new nonlinear convergence factor is put forward to improve the convergence speed and searching accuracy of the GWO algorithm, and the population with normal distribution is initialized to further improve the searching efficiency. Levy-flight is embedded to increase the randomness of global searching, so as to avoid the local optimum during the searching process. The VP&O method is used in the local searching to quickly capture the maximum power point at the global level. To verify the validity of the proposed algorithm, a PV power generation system was built for different published GWO algorithms and the ILGWO-VP&O algorithm, and these algorithms were experimentally verified. Experimental results show that the proposed ILGWO-VP&O algorithm has the fastest dynamic response speed, as well as the best steady-state control accuracy.

Photovoltaic (PV) power generation system  /  partial shadow  /  maximum power point tracking (MPPT)  /  improved grey wolf optimization (GWO) algorithm  /  variable-step perturbation & observation (VP&O) method  /  Levy-flight strategy
刘宝宏, 陈斌, 钱立峰, 史一诺, 吕莉. 改进LGWO和变步长P&O的光伏阵列功率跟踪策略. 电源学报, 2026 , 24 (4) : 110 -121 . DOI: 10.13234/j.issn.2095-2805.2026.4.110
Baohong LIU, Bin CHEN, Lifeng QIAN, Yinuo SHI, Li LÜ. Photovoltaic Array Power Tracking Strategy with Improved Levy-flight Grey Wolf Optimization and Variable-step Perturbation & Observation[J]. Journal of Power Supply, 2026 , 24 (4) : 110 -121 . DOI: 10.13234/j.issn.2095-2805.2026.4.110
Funding
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  • Jiangxi Provincial Department of Education Scientific and Technological Research Project(GJJ190954)
  • National Natural Science Foundation of China(61961025; 62066030)
  • Jiangxi Provincial Natural Science Foundation(20202BABL202001)
Appendix
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Year 2026 volume 24 Issue 4
50
13
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Article Info
doi: 10.13234/j.issn.2095-2805.2026.4.110
  • Receive Date：2024-01-04
  • Online Date：2026-10-29
  • Published：2026-04-30
Article Data
Affiliations
History
  • Received：2024-01-04
  • Revised：2024-03-07
  • Accepted：2024-03-27
Funding
Jiangxi Provincial Department of Education Scientific and Technological Research Project(GJJ190954)
National Natural Science Foundation of China(61961025; 62066030)
Jiangxi Provincial Natural Science Foundation(20202BABL202001)
Affiliations
    School of Information Engineering, Jiangxi University of Water Resources and Electric Power, Nanchang 330099, China
References
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