Please wait a minute...
文章检索
复杂系统与复杂性科学  2025, Vol. 22 Issue (1): 146-153    DOI: 10.13306/j.1672-3813.2025.01.019
  研究论文 本期目录 | 过刊浏览 | 高级检索 |
基于IDBO-IP&O算法局部遮阴下光伏系统MPPT跟踪研究
侯帅虎, 赵辉, 岳有军, 王红君
天津理工大学天津市复杂控制理论与应用重点实验室,天津 300384
MPPT Tracking of Photovoltaic Systems Under Local Shadowing Based on IDBO-IP&O Algorithm
HOU Shuaihu, ZHAO Hui, YUE Youjun, WANG Hongjun
Key Laboratory of Tianjin Complex Control Theory and Application, Tianjin University of Technology, Tianjin 300384, China
全文: PDF(8061 KB)  
输出: BibTeX | EndNote (RIS)      
摘要 为解决光伏MPPT实时跟踪问题,减少光伏阵列在局部遮阴时光伏系统输出功率的损失,提出基于改进蜣螂优化算法(IDBO)结合变步长扰动观察法(IP&O)的双层控制模型。在上层模型中将最优个体引导策略和Levy飞行引入蜣螂优化算法,动态调整区域边界,快速搜索全局最大功率点,减小跟踪波动;在下层模型采用IP&O进行局部跟踪,在保证精度的同时提高了算法收敛的实时性。通过3种复杂遮阴环境以及动态阴影环境下该算法与其他算法对比,验证了该算法在MPPTs中的有效性。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
侯帅虎
赵辉
岳有军
王红君
关键词 光伏阵列最大功率点跟踪蜣螂优化算法局部遮阳扰动观察法    
Abstract:To solve the real-time tracking problem of photovoltaic (PV) MPPT and reduce the loss of output power of the PV system when the PV array is locally shaded, a two-layer control model based on the Improved Dung Beetle Optimization Algorithm (IDBO) combined with the Variable Step Perturbation and Observation (IP&O) method is proposed. The optimal individual guidance strategy and Lévy flight are introduced into the dung beetle optimization algorithm in the upper-layer model, which dynamically adjusts the region boundaries to quickly search for the global maximum power point and reduce the tracking fluctuations; the IP&O is used in the lower-layer model for the local tracking, which ensures the accuracy and improves the real-time convergence of the algorithm at the same time. The effectiveness of this algorithm in MPPTs is verified by comparing with other algorithms in three complex shading environments and dynamic shaded environments.
Key wordsphotovoltaic array    maximum power point tracking    dung beetle optimization algorithm    partial shading    P&O
收稿日期: 2023-07-26      出版日期: 2025-04-27
ZTFLH:  TK513.5  
  TM615  
基金资助:天津市自然科学基金重点项目(08JCZDJC18600);天津市教委重点基金(2006ZD32)
通讯作者: 赵 辉(1963-),男,天津人,博士,教授,主要研究方向为复杂系统智能控制理论及应用。   
作者简介: 侯帅虎(1998-),男,河北邢台人,硕士,主要研究方向为光伏发电技术。
引用本文:   
侯帅虎, 赵辉, 岳有军, 王红君. 基于IDBO-IP&O算法局部遮阴下光伏系统MPPT跟踪研究[J]. 复杂系统与复杂性科学, 2025, 22(1): 146-153.
HOU Shuaihu, ZHAO Hui, YUE Youjun, WANG Hongjun. MPPT Tracking of Photovoltaic Systems Under Local Shadowing Based on IDBO-IP&O Algorithm[J]. Complex Systems and Complexity Science, 2025, 22(1): 146-153.
链接本文:  
https://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2025.01.019      或      https://fzkx.qdu.edu.cn/CN/Y2025/V22/I1/146
[1] SRINIVASAN A, DEVAKIRUBAKARAN S, MEENAKSHI SUNDARAM B. Mitigation of mismatch losses in solar PV system-two-step reconfiguration approach[J]. Solar Energy, 2020, 206: 640-654.
[2] RAKHSHANI E, ROUZBEHI K J. SÁNCHEZ A, et al. Integration of large scale PV-based generation into power systems: a survey[J]. Energies, 2019, 12(8): 1425.
[3] 花赟昊,朱武,郭启明.光伏发电系统MPPT算法研究综述[J].电源技术,2020,44(12):1855-1858.
HUA Y H, ZHU W, GUO Q. Review of MPPT algorithm of photovoltaic power generation system[J].Chinese Journal of Power Sources, 2020, 44(12): 1855-1858.
[4] DALI A, ABDELMALEK S, BAKDI A, et al. A novel effective nonlinear state observer based robust nonlinear sliding mode controller for a 6 kW Proton exchange membrane fuel cell voltage regulation[J]. Sustainable Energy Technologies and Assessments, 2021, 44: 100996.
[5] 荣德生,刘凤.改进型扰动观察法在光伏MPPT中的研究[J]. 电力系统及其自动化学报,2017,29(3):104-109.
RONG D S, LIU F. Application of improved perturbation and observation method to photovoltaic MPPT[J]. Proceedings of the CSU-EPSA, 2017, 29(3): 104-109.
[6] 陈景文,张文倩,李晓飞.基于改进电导增量法的MPPT控制[J].智慧电力,2021,49(9):47-55.
CHEN J W, ZHANG W Q, LI X F. Photovoltaic MPPT control based on improved conductance increment method[J]. Smart Power, 2021, 49(9):47-55.
[7] AMIR A, SELVARAJ J. Conventional and modified MPPT techniques with direct control and dual scaled adaptive step-size[J]. Solar Energy, 2017, 157: 1017-1031.
[8] ALLAHABADI S, IMAN-EINI H, FARHANGI S. Fast artificial neural network based method for estimation of the global maximum power point in photovoltaic systems[J]. IEEE Transactions on Industrial Electronics, 2022, 69(6): 5879-5888.
[9] KANWAL S, KHAN B, ALI S M, et al. Gaussian process regression based inertia emulation and reserve estimation for grid interfaced photovoltaic system[J]. Renewable Energy, 2018, 126: 865-875.
[10] LI X, GAN C, GOU K, et al. A novel WDM-MAN enabling cross-regional reconfiguration and comprehensive protection based on tangent-ring[J]. Optics Communications, 2019, 430: 416-427.
[11] HONG Y, BUAY P M P. Robust design of type-2 fuzzy logic-based maximum power point tracking for photovoltaics[J]. Sustainable Energy Technologies and Assessments, 2020, 38: 100669.
[12] DILEEP G, SINGH S M. An improved particle swarm optimization based maximum power point tracking algorithm for PV system operating under partial shading conditions[J]. Solar Energy, 2017, 158:1006-1015.
[13] 赵帅旗,肖辉,刘忠兵,等.基于CSA-IP&O的局部遮阴下光伏最大功率点追踪[J].电力系统保护与控制,2020,48(5):26-32.
ZHAO S Q, XIAO H, LIU Z B, et al. Photovoltaic maximum power point tracking under partial shading based on CSA-IP&O[J]. Power System Protection and Control, 2020, 48(5): 26-32.
[14] PRASANTH R J, RAJASEKAR N. A novel flower pollination based global maximum power point method for solar maximum power point tracking[J]. IEEE Transactions on Power Electronics, 2017, 32: 8486-8499.
[15] 李昂,刘文锋,李音柯,等.基于IP&O-ICS算法的光伏系统MPPT控制研究[J].太阳能学报,2023,44(5):203-209.
LI A, LIU W F, LI Y K, et al. Research on MPPT control of photovoltaic system based on IP&O-ICS algorithm[J]. Acta Energiae Solaris Sinica, 2023, 44(5): 203-209.
[16] MATHI D K, CHINTHAMALLA R. A hybrid global maximum power point tracking method based on butterfly particle swarm optimization and perturb and observe algorithms for a photovoltaic system under partially shaded conditions[J]. International Transactions on Electrical Energy Systems, 2020, 30(10): 1-25.
[17] XUE J, SHEN B. Dung beetle optimizer: a new meta-heuristic algorithm for global optimization[J]. The Journal of Supercomputing, 2023, 79(7): 7305-7336.
[18] HSIA S, SHEU M, JHOU J. Fast-transient high-voltage buck-boost DC-DC conversion with low overshoot[J]. Microelectronics Journal, 2021, 110: 105-119.
[19] WU C, FU J, HUANG X, et al. Lithium-ion battery health state prediction based on VMD and DBO-SVR[J]. Energies, 2023, 16(10):3993.
[20] 李斌,高鹏,郭自强.改进蜣螂算法优化LSTM的光伏阵列故障诊断[DB/OL]. [2023-11-03].https://doi.org/10.19635/j.cnki.csu-epsa.001317.
LI B, GAO P, GUO Z Q. Improved dung beetle optimizer to optimize LSTM for photovoltaic array fault diagnosis[DB/OL]. [2023-11-03].https://doi.org/10.19635/j.cnki.csu-epsa.001317.
[21] 董奕含,喻志超,胡天跃,等.基于改进蜣螂优化算法的瑞雷波频散曲线反演方法[J].油气地质与采收率,2023,30(4):86-97.
DONG Y H, YU Z C, HU T Y,et al. Inversion of Rayleigh wave dispersion curve based on improved dung beetle optimizer algorithm[J]. Petroleum Geology and Recovery Efficiency, 2023, 30(4): 86-97.
[22] 范开宇,刘艳华,杨培才,等.复杂系统中的层次结构提取与分析[J].物理学报,2022,71(17):156-163.
FAN K Y, LIU Y H, YANG P C, et al. Extraction and analysis of hierarchy in complex system[J]. Acta Physica Sinica, 71(17): 156-163.
No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed