| 引用本文: | 赵帅旗,肖辉,刘忠兵,朱梓嘉.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.[点击复制] |
| ZHAO Shuaiqi,XIAO Hui,LIU Zhongbing,ZHU Zijia.Photovoltaic maximum power point tracking under partial shading based on CSA-IP&O[J].Power System Protection and Control,2020,48(5):26-32[点击复制] |
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| 摘要: |
| 局部阴影遮挡(Partial Shading Condition, PSC)使得最大功率点追踪(Maximum Power Point Tracking, MPPT)的追踪速度和精度难以得到保证。对布谷鸟搜索算法(Cuckoo Search Algorithm, CSA)和自适应变步长的改进扰动观察法(Improved Perturbation and Observation, IP&O)进行了研究并应用到光伏的MPPT控制中。利用CSA出色的全局搜索能力快速收敛到全局最大功率点(Maximum Power Point, MPP)附近，然后利用IP&O出色的局部搜索能力快速、准确地收敛到MPP。最后设置了几种光照情况进行仿真，并用扰动观察法和粒子群(Particle Swarm Optimization, PSO)方法进行对比。通过仿真验证了所提出的方法具有更快的追踪速度和更高的精确度。 |
| 关键词: 局部阴影遮挡 布谷鸟搜索算法 最大功率点追踪 粒子群算法 扰动观察法 |
| DOI：10.19783/j.cnki.pspc.190471 |
| 投稿时间：2019-04-26修订日期：2019-07-16 |
| 基金项目:国家自然科学基金项目资助(51708194，51507014);湖南省教育厅科学研究重点项目资助(18A120) |
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| Photovoltaic maximum power point tracking under partial shading based on CSA-IP&O |
| ZHAO Shuaiqi,XIAO Hui,LIU Zhongbing,ZHU Zijia |
| (College of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410114, China;College of Civil Engineering, Hunan University, Changsha 410082, China) |
| Abstract: |
| Partial shading condition makes the tracking speed and accuracy of maximum power point tracking difficult to guarantee. The Cuckoo Search Algorithm (CSA) and the Improved Perturbation and Observation (IP&O) method of adaptive variable step are studied and applied to the MPPT control of the PV system. The excellent global search capability of the CSA is used to converge near the global Maximum Power Point (MPP) quickly, then the excellent local search capability of adaptive variable step Perturbation and Observation (P&O) is used to converge to the MPP quickly and accurately. Finally, several lighting conditions are set up for simulation and P&O and Particle Swarm Optimization (PSO) algorithms are compared. Simulation results indicate that the proposed method has faster tracking speed and higher accuracy. This work is supported by National Natural Science Foundation of China (No. 51708194 and No. 51507014) and Key Project of Scientific Research for Hunan Education Department (No. 18A120). |
| Key words: partial shading condition cuckoo search algorithm maximum power point tracking particle swarm optimization perturbation and observation |
