粒子群与电导增量法结合的光伏发电MPPT

doi:10.16182/j.issn1004731x.joss.201612017

系统仿真学报 ›› 2016, Vol. 28 ›› Issue (12): 2994-3000.doi: 10.16182/j.issn1004731x.joss.201612017

粒子群与电导增量法结合的光伏发电MPPT

余运俊^1,2, 刘涛¹, 王时胜¹, 辛建波², 聂晓华¹

1.南昌大学,江西南昌 330031;
2.江西省电力科学研究院,江西南昌 330096

收稿日期:2015-04-13 修回日期:2015-07-09 出版日期:2016-12-08 发布日期:2020-08-13
作者简介:余运俊(1978-),男,江西上饶,博士,副教授,研究方向为光伏发电,低碳电力等。
基金资助:
国家自然科学基金(61563034, 51467013),国家国际科技合作专项(2014DFG72240),国家科技支撑计划(2013BAA01B01),江西省自然科学基金(20151BABE206051)

Global optimized Photovoltaic MPPT Algorithm Based on PSO and Incremental Conductance Method

Yu Yunjun^1,2, Liu Tao¹, Wang Shisheng¹, Xin Jianbo², Nie Xiaohua¹

1. Nanchang University, Nanchang 330031, China;
2. Jiangxi Electric Power Research Institute, Nanchang 330096, China

Received:2015-04-13 Revised:2015-07-09 Online:2016-12-08 Published:2020-08-13

摘要/Abstract

摘要： 光伏阵列在局部阴影遮蔽时其P-V特性曲线会呈现出多个局部峰值的情况,电导增量法可能跟踪在某个并非最大的极值点上,从而造成跟踪失败。粒子群算法有全局寻优的特点,但跟踪精度有欠缺。提出了一种基于电导增量法优化的粒子群全局MPPT算法,粒子群算法能够快速跟踪到全局最大功率点附近,电导增量法可以进一步精确跟踪到最大功率点。通过将所提方法与传统电导增量法simulink仿真对比以及当局部阴影情况发生突变时的研究,结果证明了该方法能快速准确地跟踪到光伏阵列全局最大功率点。

关键词: 光伏阵列, 局部阴影, 电导增量法, 粒子群算法, 多峰值最大功率点

Abstract: The P-V array characteristic curve exhibits a plurality of local maximum power point under conditions of partial shading. The incremental conductance method maybe track an extreme value point that is not the largest power point, thus lead to tracking failure. The PSO algorithm has the characteristics of global optimization, but its tracking precision is deficient. A global MPPT algorithm based on PSO algorithm by incremental conductance method was proposed, PSO algorithm could quickly locate to the approximate global MPP, INC could further precise the MPP. Compared to the traditional incremental conductance method Simulink simulation and the research when partial shade suddenly changed, the result shows that the present method can track the global MPP of the PV array quickly and accurately.

Key words: PV array, partial shading, INC, PSO algorithm, Multi-peak MPP

中图分类号:

TM615

余运俊, 刘涛, 王时胜, 辛建波, 聂晓华. 粒子群与电导增量法结合的光伏发电MPPT[J]. 系统仿真学报, 2016, 28(12): 2994-3000.

Yu Yunjun, Liu Tao, Wang Shisheng, Xin Jianbo, Nie Xiaohua. Global optimized Photovoltaic MPPT Algorithm Based on PSO and Incremental Conductance Method[J]. Journal of System Simulation, 2016, 28(12): 2994-3000.

参考文献

[1] 聂晓华, 赖家俊. 局部阴影光伏阵列全局最大功率点跟踪控制方法综述[J]. 电网技术, 2014, 38(12): 3279-3285.
(Nie Xiaohua, Lai Jiajun.A Survey on Tracking and Control Approaches for Global Maximum Power Point of Photovoltaic Arrays in Partially Shaded Environment[J]. Power System Technology (S1000-3673), 2014, 38(12): 3279-3285.)
[2] 周林, 武剑, 栗秋华, 等. 光伏阵列最大功率点跟踪控制方法综述[J]. 高电压技术, 2008, 3(6): 1145-1154.
(Zhou Lin, Wu Jian, Li Qiuhua, et al.Survey of Maximum Power Point Tracking Techniques for Photovoltaic Array[J]. High Voltage Engineering (S1003-6520), 2008, 3(6): 1145-1154.)
[3] Femia N, Lisi G, Petrone G, et al.Distributed Maximum Power Point Tracking of Photovoltaic Arrays: Novel Approachand System Analysis[J]. IEEE Transactions On Industrial Electronics (S0278-0046), 2008, 55(7): 2610-2621.
[4] Miyatake M, Veerachary M, Toriumi F.Maximum power point tracking of multiple photovoltaic arrays: a PSO approach[J]. IEEE Transactions on Aerospace and Electronic Systems (S0018-9251), 2011, 47(1): 367-380.
[5] 余运俊, 张翔, 王时胜, 等. 电导增量法光伏发电MPPT研究综述[J]. 电源技术, 2014, 38(12): 2440-2444.
(Yu Yunjun, Zhang Xiang, Wang Shisheng et al. Review of incremental conductance method for photovoltaic power generation MPPT[J]. Chinese Journal of Power Sources (S1002-087X), 2014, 38(12): 2440-2444.)
[6] 崔岩, 白静晶. 光伏阵列多峰值最大功率点跟踪研究[J]. 电机与控制学报, 2012, 16(6): 87-91.
(Cui yan, Bai Jing jing. Research on multi-peak PV model maximum power point tracking[J]. Electric Machines and Control (S1007-449X), 2012, 16(6): 87-91.)
[7] Ji Y H, Jung D Y, Kim J G, et al.A real maximum power point tracking method for mismatching compensation in PV array under partially shaded conditions[J]. IEEE Transactions on Power Electronics (S0885-8993), 2011, 26(4): 1001-1009.
[8] Alajmi B N, Ahmed K H, Finney S J, et al.A maximum power point tracking technique for partially shaded photovoltaic systems in microgrids[J]. IEEE Transactions on Industrial Electronics (S0278-0046), 2013, 60(4): 1596-1606.
[9] Patel H, Agarwal V.Maximum power point tracking scheme for PV systems operating under partially shaded conditions[J]. IEEE Transactions on Industrial Electronics (S0278-0046), 2008, 55(4): 1689-1698.
[10] 刘晓艳, 祁新梅, 郑寿森, 等. 局部阴影条件下光伏阵列仿真模型的研究[J]. 系统仿真学报, 2012, 24(5): 1125-1131.
(Liu Xiaoyan, Qi Xinmei, Zhen Shousen, et al.Study on Simulation Model of PV Array Under Partially Shading[J]. Journal of System Simulation (S1004-731X), 2012, 24(5): 1125-1131.)
[11] 陈如亮, 崔岩, 李大勇, 等. 光照不均匀情况下光伏组件仿真模型的研究[J]. 系统仿真学报, 2008, 20(7): 1681-1690.
(CHEN Ru-Liang, CUI Yan, LI Da-yong, HU Hong-xun.Study on Simulation Model of PV Module under Non-uniform Isolation[J]. Journal of System Simulation (S1004-731X), 2008, 20(7): 1681-1690.)
[12] 刘晓艳, 祁新梅, 郑寿森, 等. 局部阴影条件下光伏阵列的建模与分析[J]. 电网技术, 2010, 34(11): 192-197.
(Liu XiaoYan, QiXinmei, Zhen Shousen,et al. Model and Analysis of Photovoltaic Array Under Partial Shading[J]. Power System Technology (S1000-3673), 2010, 34(11): 192-197.)
[13] Roy C S, Saha H.Maximum power point tracking of partially shaded solar photovoltaic arrays[J]. Solar Energy Materials and Solar Cells (S0927-0248), 2010, 94(9): 1441-1447.
[14] 陈侃, 冯琳, 贾林壮, 等. 光伏系统在局部阴影条件下避免困于局部最大功率点跟踪算法研究[J]. 可再生能源, 2013, 31(1): 13-16.
(Chen Kan, Feng Lin, Jia Linzhuang, et al.Research on an optimized maximum power point tracking algorithm avoiding local under Partial Shaded conditions in photovoltaic system[J]. Renewable Energy Resources (S1671-5292), 2013,31(1): 13-16.)
[15] 孙博, 梅军, 郑建勇. 局部阴影条件下最大功率点跟踪改进算法[J]. 电力自动化设备, 2014, 34(1): 115-119.
(Sun Bo, Mei Jun, Zheng Jianyong.Improved MPPT Method Under Partial Shading Conditions[J]. Electric Power Automation Equipment (S1006-6047), 2014, 34(1): 115-119.)
[16] Li Zhonghua, He Chunhui, Tan Hongzhou.Artificial immune network with social learning and its application in FIR filter designing[J]. Applied Soft Computing (S1568-4946), 2013, 13(12): 4557-4569.
[17] 李天博, 褚俊, 陈坤华. 基于粒子群算法的MPPT仿真及应用[J]. 电力电子技术, 2012, 46(1): 7-9.
(Li Tianbo, Chu Jun, Chen Kunhua.Maximum Power Point Tracking Simulation and Application Based on Particle Swarm Optimization[J]. Power Electronics (S1000-100X), 2012, 46(1): 7-9.)
[18] 朱艳伟, 石新春, 但扬清, 等. 粒子群优化算法在光伏阵列多峰最大功率点跟踪中的应用[J]. 中国电机工程学报, 2012, 32(4): 42-48.
(Zhu Yanwei, Shi Xinchu, Dan Yangqing, et al.Application of PSO Algorithm in Global MPPT for PV Array[J]. Proceedings of the CSEE (S0258-8013), 2012, 32(4): 42-48.)
[19] 惠晶, 王思杰, 谢伟, 等. 粒子群优化在光伏系统MPPT控制中的应用[J]. 电力电子技术, 2012, 46(5): 31-33.
(Hui Jing, Wang Sijie, Xie Wei, et al.Application of PV-MPPT Control Based on Particle Swarm Optimization[J]. Power Electronics (S1000-100X), 2012, 46(5): 31-33.)
[20] 赵阳, 符强, 王镭, 等. 基于粒子群算法的最大功率点跟踪方法研究[J]. 电力电子技术, 2010, 44(6): 32-33.
(Zhao Yang, Fu Qiang, Wang Lei, et al.The Maximum Power Point Tracking of Solar Cell Based on PSO Algorithm[J]. Power Electronics (S1000-100X), 2010, 44(6): 32-33.)
[21] 王雨, 胡仁杰. 基于粒子群优化和爬山法的MPPT算法[J]. 太阳能学报, 2014, 35(1): 149-153.
(Wang Yu, Hu Renjie.MPPT Algorithm Based on Particle Swarm Optimization With Hill Climbing Method[J]. Acta Energiae Solaris Sinica (S0254-0096), 2014, 35(1): 149-153.)
[22] Ishaque K, Salam Z, Amjad M, et al.An improved particle swarm optimization (PSO)-based MPPT for PV with reduced steady state oscillation[J]. IEEE Transactions on Power Electronics (S0885-8993), 2012, 27(8): 3627-3638.
[23] Ishaque K, Salam Z, Shamsudin A, et al.A direct control based maximum power point tracking method for photovoltaic system under partial shading conditions using particle swarm optimization algorithm[J]. Applied Energy (S0306-2619), 2012, 99(11): 414-422.

粒子群与电导增量法结合的光伏发电MPPT

Global optimized Photovoltaic MPPT Algorithm Based on PSO and Incremental Conductance Method

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