| 基于粒子群优化算法和电导增量法的多峰值MPPT控制 |
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| 引用本文： | 杨海柱,岳刚伟,康乐.基于粒子群优化算法和电导增量法的多峰值MPPT控制[J].电源学报,2019,17(6):128-136. |
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| 作者姓名： | 杨海柱 岳刚伟 康乐 |
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| 作者单位： | 河南理工大学电气工程与自动化学院, 焦作 454000,河南理工大学电气工程与自动化学院, 焦作 454000,河南理工大学电气工程与自动化学院, 焦作 454000 |
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| 基金项目： | 国家自然科学基金资助项目（U1504623） |
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| 摘 要： | 复杂环境条件下,光伏阵列由于被遮挡其输出特性呈现多峰值特性,传统最大功率点跟踪MPPT(maximum power point tracking)算法不再适用。为此,在研究光伏阵列多峰值输出特性的基础上,提出一种基于粒子群优化PSO(particle swarm optimization)算法和电导增量法INC(incremental conductance)的多峰值MPPT算法。该算法分成2步:第1步先由PSO算法将输入位置调整到最优值附近;第2步再由INC算法得到全局最优解,其中对传统PSO算法进行改进,INC算法采用变步长扰动。在Matlab中进行仿真,结果表明该算法可实现复杂环境条件下的最大功率跟踪,并具备较快的响应速度和稳定的寻优效果。
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| 关 键 词： | 复杂环境 多峰值MPPT 粒子群优化算法 电导增量法 |
| 收稿时间： | 2018/5/7 0:00:00 |
| 修稿时间： | 2018/12/27 0:00:00 |
Multi-peak MPPT Control Based on PSO and INC Algorithms |
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| YANG Haizhu,YUE Gangwei and KANG Le.Multi-peak MPPT Control Based on PSO and INC Algorithms[J].Journal of power supply,2019,17(6):128-136. |
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| Authors: | YANG Haizhu YUE Gangwei and KANG Le |
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| Affiliation: | School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454000, China,School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454000, China and School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454000, China |
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| Abstract: | Under complex environmental conditions, the traditional maximum power point tracking(MPPT) algorithm is no longer applicable due to the multi-peak characteristics of output from a PV array caused by shading. To solve this problem, a multi-peak MPPT algorithm based on particle swarm optimization(PSO) and incremental conductance(INC) algorithms is proposed. This algorithm is divided into two steps:the first step is to adjust the input position to near the optimal value by using the PSO algorithm, and the second step is to obtain a global optimal solution by using the INC algorithm. Specifically, the traditional PSO algorithm is improved, and the INC algorithm uses a variable-step size. Simulation results in Matlab show that the proposed algorithm can achieve the maximum power tracking under complex environmental conditions; in addition, it has a faster response speed and stable optimization results. |
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| Keywords: | complex environment multi-peak maximum power point tracking(MPPT) particle swarm optimization(PSO) algorithm incremental conductance(INC) algorithm |
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