复杂光照条件下光伏阵列的THW-GWO-P&#x00026;O复合MPPT控制

顾吉鹏; 王舒宜; 汪斌杰; 张有兵; 张志明; 沈成宇

doi:10.19912/j.0254-0096.tynxb.2024-1662

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太阳能学报 ›› 2026, Vol. 47 ›› Issue (1) : 116-126. DOI: 10.19912/j.0254-0096.tynxb.2024-1662

复杂光照条件下光伏阵列的THW-GWO-P&O复合MPPT控制

顾吉鹏¹, 王舒宜¹, 汪斌杰², 张有兵¹, 张志明³, 沈成宇³

作者信息 +

THW-GWO-P&O COMPOSITE MPPT CONTROL OF PHOTOVOLTAIC ARRAYS UNDER COMPLEX LIGHTING CONDITIONS

Gu Jipeng¹, Wang Shuyi¹, Wang Binjie², Zhang Youbing¹, Zhang Zhiming³, Shen Chengyu³

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文章历史 +

摘要

提出一种由双狼牵头改进的灰狼算法（THW-GWO）与扰动观察法（P&O）相结合的最大功率点跟踪（MPPT）控制方法,用以提升光伏阵列的能源利用率。首先,对光伏阵列在复杂光照下的发电原理及MPPT控制原理进行深入分析,从理论的角度说明P&O跟踪效率较低的原因。其次,将GWO与P&O结合用于提升光伏阵列MPPT控制的跟踪效率。同时为了在GWO收敛速度、寻找局部最优解等方面达到更好的效果,在GWO的收敛因子、加权距离和位置更新权重方面做出自适应调整,即THW-GWO。最后,通过Matlab/Simulink仿真平台对光伏阵列在P&O、GWO、THW-GWO、THW-GWO-P&O 4种MPPT方法下的控制效果进行对比分析,结果表明THW-GWO-P&O在均匀光照和局部遮阴条件下均展现了更高的能量转换效率、寻优精度和收敛速度,验证THW-GWO-P&O具有更好的寻优性能。

Abstract

A maximum power point tracking （MPPT） control method combining the twin-wolf-driven gray wolf optimization （THW-GWO） with perturbation and observation （P&O） is proposed to enhance the energy utilization efficiency of photovoltaic arrays. First, an in-depth analysis is conducted on the power generation principles of photovoltaic arrays under complex illumination conditions and the MPPT control principles, theoretically explaining the reasons for the relatively low tracking efficiency of P&O. Second, GWO and P&O are integrated to improve the tracking efficiency of MPPT control for photovoltaic arrays. To achieve better performance in terms of GWO convergence speed and local optimal solution search, adaptive adjustments are made to the convergence factor, weighted distance, and position update weight of GWO, resulting in THW-GWO. Finally, the control performance of photovoltaic arrays under P&O, GWO, THW-GWO, and THW-GWO-P&O is compared and analyzed in Matlab/Simulink. Results demonstrate that THW-GWO-P&O achieves higher energy conversion efficiency, optimization accuracy, and convergence speed under both uniform illumination and partial shading conditions, validating its superior optimization performance.

导出引用

顾吉鹏, 王舒宜, 汪斌杰, 张有兵, 张志明, 沈成宇. 复杂光照条件下光伏阵列的THW-GWO-P&O复合MPPT控制[J]. 太阳能学报. 2026, 47(1): 116-126 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1662

Gu Jipeng, Wang Shuyi, Wang Binjie, Zhang Youbing, Zhang Zhiming, Shen Chengyu. THW-GWO-P&O COMPOSITE MPPT CONTROL OF PHOTOVOLTAIC ARRAYS UNDER COMPLEX LIGHTING CONDITIONS[J]. Acta Energiae Solaris Sinica. 2026, 47(1): 116-126 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1662

中图分类号： TM615

参考文献

[1] 梅生伟, 郭永庆, 司杨, 等. 太阳能热气流发电技术及其应用展望[J]. 高电压技术, 2019, 45(11): 3401-3412.MEI S W, GUO Y Q, SI Y, et al. Progress of researches on solar chimney power generation technology and its application[J]. High voltage engineering, 2019, 45(11): 3401-3412.
[2] 解宝, 李萍宇, 苏绎仁, 等. 局部阴影下光伏阵列的最大功率点跟踪算法研究[J]. 太阳能学报, 2023, 44(12): 47-52.XIE B, LI P Y, SU Y R, et al. Research on maximum power point tracking algorithm of PV array under local shadow[J]. Acta energiae solaris sinica, 2023, 44(12): 47-52.
[3] ÇAKMAK F, AYDOĞMUŞ Z, TÜR M R. Analysis of open circuit voltage MPPT method with analytical analysis with perturb and observe (P&O) MPPT method in PV systems[J]. Electric power components and systems, 2024, 52(9): 1528-1542.
[4] SHANG L Q, GUO H C, ZHU W W.An improved MPPT control strategy based on incremental conductance algorithm[J]. Protection and control of modern power systems, 2020, 5(2): 1-8.
[5] ZHOU X Y, ZHANG Y, MA X, et al.Performance characteristics of photovoltaic cold storage under composite control of maximum power tracking and constant voltage per frequency[J]. Applied energy, 2022, 305: 117840.
[6] 吴玲, 张秀锦, 刘秋华, 等. 基于多元宇宙优化算法的光伏发电MPPT控制算法[J]. 太阳能学报, 2023, 44(9): 204-211.WU L, ZHANG X J, LIU Q H, et al. MPPT control algorithm of photovoltaic power generation based on multi-verse optimization algorithm[J]. Acta energiae solaris sinica, 2023, 44(9): 204-211.
[7] JANG Y, LEE C, BAE S.Linear-extrapolation-based gray-wolf optimization algorithm for global maximum power tracking of thermoelectric generators[C]//2024 IEEE Power & Energy Society General Meeting (PESGM). Seattle, WA, USA, 2024: 1.
[8] 毛明轩, 许钊, 崔立闯, 等. 基于改进灰狼优化算法的光伏阵列多峰MPPT研究[J]. 太阳能学报, 2023, 44(3): 450-456.MAO M X, XU Z, CUI L C, et al. Research on multi-peak MPPT of photovoltaic array based on modified gray wolf optimization algorithm[J]. Acta energiae solaris sinica, 2023, 44(3): 450-456.
[9] MOHANTY S, SUBUDHI B, RAY P K.A new MPPT design using grey wolf optimization technique for photovoltaic system under partial shading conditions[J]. IEEE transactions on sustainable energy, 2016, 7(1): 181-188.
[10] 龙文, 蔡绍洪, 焦建军, 等. 一种改进的灰狼优化算法[J]. 电子学报, 2019, 47(1): 169-175.LONG W, CAI S H, JIAO J J, et al. An improved grey wolf optimization algorithm[J]. Acta electronica sinica, 2019, 47(1): 169-175.
[11] ÁGUILA-LEÓN J, VARGAS-SALGADO C, DÍAZ-BELLO D, et al. Optimizing photovoltaic systems: a meta-optimization approach with GWO-Enhanced PSO algorithm for improving MPPT controllers[J]. Renewable energy, 2024, 230: 120892.
[12] 欧云, 周恺卿, 尹鹏飞, 等. 双收敛因子策略下的改进灰狼优化算法[J]. 计算机应用, 2023, 43(9): 2679-2685.OU Y, ZHOU K Q, YIN P F, et al. Improved grey wolf optimizer algorithm based on dual convergence factor strategy[J]. Journal of computer applications, 2023, 43(9): 2679-2685.
[13] 高放, 胡嵘昭, 殷林飞, 等. 基于定位收缩法的局部阴影条件下光伏最大功率点跟踪[J]. 电力系统保护与控制, 2024, 52(4): 87-99.GAO F, HU R Z, YIN L F, et al. Locate and shrink method for PV maximum power point tracking in partial shading conditions[J]. Power system protection and control, 2024, 52(4): 87-99.
[14] ZIDANE T E K, AZIZ A S, ZAHRAOUI Y, et al. Grid-connected solar PV power plants optimization: a review[J]. IEEE access, 2023, 11: 79588-79608.
[15] 董存, 王铮, 白捷予, 等. 光伏发电功率超短期预测方法综述[J]. 高电压技术, 2023, 49(7): 2938-2951.DONG C, WANG Z, BAI J Y, et al. Review of ultra-short-term forecasting methods for photovoltaic power generation[J]. High voltage engineering, 2023, 49(7): 2938-2951.
[16] LI X S, ZHU Y X, WEN H Q, et al.Reference-voltage-line-aided power incremental algorithm for photovoltaic GMPPT and partial shading detection[J]. IEEE transactions on sustainable energy, 2022, 13(3): 1756-1770.
[17] 王仁明, 张铭锐, 鲍刚, 等. 基于拟合反演滑模方法的光伏系统MPPT控制[J]. 太阳能学报, 2023, 44(8): 224-231.WANG R M, ZHANG M R, BAO G, et al. MPPT control of photovoltaic system based on fitting backstepping sliding mode method[J]. Acta energiae solaris sinica, 2023, 44(8): 224-231.
[18] ABDEL-SALAM M, EL-MOHANDES M T, EL-GHAZALY M. An efficient tracking of MPP in PV systems using a newly-formulated P&O-MPPT method under varying irradiation levels[J]. Journal of electrical engineering & technology, 2020, 15(1): 501-513.
[19] MIRZA A F, LING Q, JAVED M Y, et al.Novel MPPT techniques for photovoltaic systems under uniform irradiance and partial shading[J]. Solar energy, 2019, 184: 628-648.
[20] OSTADRAHIMI A, MAHMOUD Y.Novel spline-MPPT technique for photovoltaic systems under uniform irradiance and partial shading conditions[J]. IEEE transactions on sustainable energy, 2021, 12(1): 524-532.
[21] 薛阳, 燕宇铖, 贾巍, 等. 基于改进灰狼算法优化长短期记忆网络的光伏功率预测[J]. 太阳能学报, 2023, 44(7): 207-213.XUE Y, YAN Y C, JIA W, et al. Photovoltaic power prediction model based on IGWO-LSTM[J]. Acta energiae solaris sinica, 2023, 44(7): 207-213.
[22] 赵云. 基于改进灰狼算法的配电网储能优化配置[J]. 太阳能学报, 2023, 44(10): 584.ZHAO Y. Optimal allocation of energy storage in distribution network based on improved grey wolf algorithm[J]. Acta energiae solaris sinica, 2023, 44(10): 584.
[23] 董志强, 郑凌蔚, 苏然, 等. 一种基于IGWO-SNN的光伏出力短期预测方法[J]. 电力系统保护与控制, 2023, 51(1): 131-138.DONG Z Q, ZHENG L W, SU R, et al. An IGWO-SNN-based method for short-term forecast of photovoltaic output[J]. Power system protection and control, 2023, 51(1): 131-138.
[24] GUO K, CUI L C, MAO M X, et al.An improved gray wolf optimizer MPPT algorithm for PV system with BFBIC converter under partial shading[J]. IEEE access, 2020, 8: 103476-103490.
[25] 付文龙, 孟嘉鑫, 张赟宁, 等. 复杂遮荫下基于改进GWO的光伏多峰MPPT控制[J]. 太阳能学报, 2023, 44(3): 435-442.FU W L, MENG J X, ZHANG Y N, et al. Photovoltaic multi-peak MPPT control based on improved gwo under complex shade[J]. Acta energiae solaris sinica, 2023, 44(3): 435-442.