基于拟合反演滑模方法的光伏系统MPPT控制

王仁明; 张铭锐; 鲍刚; 刘闻仲; 杨婕

doi:10.19912/j.0254-0096.tynxb.2022-0487

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太阳能学报 ›› 2023, Vol. 44 ›› Issue (8) : 224-231. DOI: 10.19912/j.0254-0096.tynxb.2022-0487

基于拟合反演滑模方法的光伏系统MPPT控制

王仁明, 张铭锐, 鲍刚, 刘闻仲, 杨婕

作者信息 +

MPPT CONTROL OF PHOTOVOLTAIC SYSTEM BASED ON FITTING BACKSTEPPING SLIDING MODE METHOD

Wang Renming, Zhang Mingrui, Bao Gang, Liu Wenzhong, Yang Jie

Author information +

文章历史 +

摘要

该文提出一种基于拟合优化的反演滑模控制的混合MPPT方案。该方案首先根据光伏发电系统的P-V特征曲线,使用3次插值函数来拟合最大功率点处的参考电压,然后基于参考电压以及反演滑模控制原理,设计相应的控制器并通过PWM调制控制占空比,使之在不同的环境条件下能迅速有效跟踪最大功率点。最后,通过Matlab/Simulink仿真验证所提出优化方案的有效性,并与其他经典方法进行对比分析。结果显示,该方法跟踪速度快、稳态功率波动小,跟踪性能优异。

Abstract

A hybrid MPPT scheme based on fitting optimization backstepping sliding mode control is proposed in this paper. Firstly, the scheme is based on the P-V characteristic curve of photovoltaic power generation system. The cubic interpolation function is used to fit the reference voltage at the maximum power point V_ref. Then, based on the V_ref and backstepping sliding mode control principle, a controller is designed and the duty cycle is controlled by PWM modulation, so that the controller can track the maximum power point quickly and effectively under different environmental conditions. Finally, the effectiveness of the proposed scheme is verified by Matlab/Simulink simulation, and compared with other classical methods. The results show that the method has high tracking speed, low steady-state power fluctuation and better tracking performance.

导出引用

王仁明, 张铭锐, 鲍刚, 刘闻仲, 杨婕. 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 https://doi.org/10.19912/j.0254-0096.tynxb.2022-0487

Wang Renming, Zhang Mingrui, Bao Gang, Liu Wenzhong, Yang Jie. MPPT CONTROL OF PHOTOVOLTAIC SYSTEM BASED ON FITTING BACKSTEPPING SLIDING MODE METHOD[J]. Acta Energiae Solaris Sinica. 2023, 44(8): 224-231 https://doi.org/10.19912/j.0254-0096.tynxb.2022-0487

中图分类号： TK513.5

参考文献

[1] 王丰, 孔鹏举, Fred C.Lee, 等. 基于分布式最大功率跟踪的光伏系统输出特性分析[J]. 电工技术学报, 2015, 30(24): 127-134.
WANG F, KONG P J, LEE F C, et al.Output characteristic analysis of distributed maximum power point tracking PV system[J]. Transactions of China Electrotechnical Society, 2015, 30(24): 127-134.
[2] 刘东冉, 陈树勇, 马敏, 等. 光伏发电系统模型综述[J]. 电网技术, 2011, 35(8):47-52.
LIU D R, CHEN S Y, MA M, et al.A review on models for photovoltaic generation system[J]. Power system technology, 2011, 35(8): 47-52.
[3] 赖昌伟, 黎静华, 陈博, 等. 光伏发电出力预测技术研究综述[J]. 电工技术学报, 2019, 34(6): 1201-1217.
LAI C W, LI J H, CHEN B, et al.Review of photovoltaic power output prediction technology[J]. Transactions of China Electrotechnical Society, 2019, 34(6): 1201-1217.
[4] 崔岩, 蔡炳煌, 李大勇, 等. 太阳能光伏系统MPPT控制算法的对比研究[J]. 太阳能学报, 2006, 27(6): 535-539.
CUI Y, CAI B H, LI D Y, et al.Comparative studies on the MPPT control algorithms of solar energy photovoltaic system[J]. Acta energiae solaris sinica, 2006, 27(6): 535-539.
[5] VILLALVA M G, GAZOLI J R, FILHO E R.Comprehensive approach to modeling and simulation of photovoltaic arrays[J]. IEEE transactions on power electronics, 2009, 24(5): 1198-1208.
[6] 彭志辉, 彭玉春, 周宏明, 等. 光照快速变化下MPPT算法扰动步长的优化设计[J]. 太阳能学报, 2020, 41(8): 137-143.
PENG Z H, PENG Y C, ZHOU H M, et al.Optimal design of MPPT algorithm perturbation step length under rapid change solar radiation[J]. Acta energiae solaris sinica, 2020, 41(8): 137-143.
[7] 梅润杰, 张经炜. 基于Z源逆变器的粒子群和模糊变步长电导增量MPPT算法[J]. 太阳能学报, 2020, 41(1): 137-145.
MEI R J, ZHANG J W.MPPT algorithn of particle swarm optimization and fuzzy variable step incremental conductance based on Z-source inverter[J]. Acta energiae solaris sinica, 2020, 41(1): 137-145.
[8] 魏立明, 吴扬昀. 基于改进电导增量法的光伏MPPT策略研究[J]. 电源技术, 2021, 45(6): 791-796.
WEI L M, WU Y Y.Research on maximum power point tracking of photovoltaic power system based on improved conductance increment method[J]. Chinese journal of power sources, 2021, 45(6): 791-796.
[9] MIRZE A F, MANSOOR M, LING Q, et al.Advanced variable step size incremental conductance MPPT for a standalone PV system utilizing a GA-tuned PID controller[J]. Energies, 2020, 13(16): 4153.
[10] 武迪, 许春雨, 郑丽君, 等. 基于β参数的光伏系统最大功率点跟踪算法研究[J]. 太阳能学报, 2020, 41(6) :234-241.
WU D, XU C Y, ZHENG L J, et al.Maximum power point tracking algorithm of photovoltaic system based on β parameter[J]. Acta energiae solaris sinica, 2020, 41(6): 234-241.
[11] 商立群, 朱伟伟. 基于全局学习自适应细菌觅食算法的光伏系统全局最大功率点跟踪方法[J]. 电工技术学报, 2019, 34(12): 2606-2614.
SHANG L Q, ZHU W W.Photovoltaic system global maximum power point tracking method based on the global learning adaptive bacteria foraging algorithm[J]. Transactions of China Electrotechnical Society, 2019, 34(12): 2606-2614.
[12] 张明锐, 陈喆旸, 韦莉. 免疫萤火虫算法在光伏阵列最大功率点跟踪中的应用[J]. 电工技术学报, 2020, 35(7): 1553-1562.
ZHANG M R, CHEN Z Y, WEI L.Application of immune firefly algorithms in photovoltaic array maximum power point tracking[J]. Transactions of China Electrotechnical Society, 2020, 35(7): 1553-1562.
[13] 赵斌, 袁清, 王力, 等. 基于改进蚁狮算法的光伏多峰值MPPT控制[J]. 太阳能学报, 2021, 42(9): 132-139.
ZHAO B, YUAN Q, WANG L, et al.Multi-peak MPPT control of PV array based on improved alo algorithm[J]. Acta energiae solaris sinica, 2021, 42(9): 132-139.
[14] ELOBAID L M, ABDELSALAM A K, ZAKZOUK E E.Artificial neural network-based photovoltaic maximum power point tracking techniques: a survey[J]. IET renewable power generation, 2015, 9(8): 1043-1063.
[15] 李畸勇, 张伟斌, 赵新哲, 等. 改进鲸鱼算法优化支持向量回归的光伏最大功率点跟踪[J]. 电工技术学报, 2021, 36(9): 1771-1781.
LI J Y, ZHANG W B, ZHAO X Z, et al.Global maximum power point tracking for PV array based on support vector regression optimized by improved whale algorithm[J]. Transactions of China Electrotechnical Society, 2021, 36(9): 1771-1781.
[16] ZAFAR M H, KHAN N M, MIRZA A F, et al.Bio-inspired optimization algorithms based maximum power point tracking technique for photovoltaic systems under partial shading and complex partial shading conditions[J]. Journal of cleaner production, 2021, 309: 127279.
[17] 方番, 李媛. 储能型准Z源逆变器的积分滑模电流控制策略[J]. 电网技术, 2018, 42(9): 2967-2975.
FANG F, LI Y.Integrated sliding-mode current control strategy for energy-stored quasi-Z-source inverter[J]. Power system technology, 2018, 42(9): 2967-2975.
[18] 靳艳华, 惠晶, 谢伟. 基于滑模变结构PI控制的光伏系统MPPT研究[J]. 电源技术, 2014, 38(12): 2389-2392.
JIN Y H, HUI J, XIE W.Novel hybrid control of MPPT method based on sliding mode variable structure and PI strategyl[J]. Chinese journal of power sources, 2014, 38(12): 2389-2392.
[19] 谢奇爱. 面向光伏最大功率跟踪的改进滑模控制方法[J]. 太阳能学报, 2020, 41(10): 381-388.
XIE Q A.Improved sliding mode control method for photovoltaic maximum power tracking[J]. Acta energiae solaris sinica, 2020, 41(10): 381-388.
[20] AHMAD KHAN Z, KHAN L, AHMAD S, et al.RBF neural network based backstepping terminal sliding mode MPPT control technique for PV system[J]. PLoS one, 2021, 16(4): e0249705.