基于改进差分进化算法的光伏最大功率点跟踪  

Photovoltaic Maximum Power Point Tracking Based on Improved Differential Evolution Algorithm

作　　者：葛传九 武鹏[1] 金俊喆 董祥祥 楼琦凯 GE Chuanjiu;WU Peng;JIN Junzhe;DONG Xiangxiang;LOU Qikai(College of Electronic and Electrical Engineering,Shanghai University of Engineering Science,Shanghai 201620,China)

机构地区：[1]上海工程技术大学电子电气工程学院,上海201620

出　　处：《电子科技》2022年第9期15-21,共7页Electronic Science and Technology

基　　金：上海市自然科学基金(18ZR141670);上海工程技术大学研究生科研创新项目(20KY0212)。

摘　　要：在光伏最大功率点跟踪算法中,传统算法收敛会产生陷入局部极值的问题,而智能算法收敛较慢,且在收敛过程中可能产生大幅度电压振荡。针对上述问题,文中提出了相应的改进策略。在粒子群算法迭代过程中,通过增加粒子种群的个体排序来抑制大幅度电压振荡,消除较差适应值粒子对速度更新的影响,同时结合差分进化算法中种群更新时的竞争关系来提高收敛速度。采用单峰值及多峰值算例对所提策略进行仿真实验,得到的光伏最大功率分别为60 W和122 W。仿真结果表明,相较于粒子群算法和差分进化算法,文中所提算法的收敛速度分别提升了52.22%和61.60%,追踪过程的中期电压波动幅度分别减少了15%和30%。For the photovoltaic maximum power point tracking algorithm,the convergence of traditional algorithms will cause the problem of trapping into local extremes,while the convergence of intelligent algorithms is slow,and may produce large amplitude voltage oscillation in the process of convergence.In view of the above-mentioned problems,the study proposes corresponding improvement strategies.In the iterative process of particle swarm optimization,the individual order of the population is added to suppress the large amplitude voltage oscillation,the influence of the particles with poor fitness on the speed update is eliminated,and the convergence speed is improved through combining the competitive relationship during population update in the differential evolution algorithm.Single-peak and multi-peak examples are used to simulate the proposed strategy,and the maximum photovoltaic power obtained is 60 W and 122 W,respectively.The simulation results show that compared with particle swarm optimization and differential evolution algorithm,the proposed algorithm improves the convergence speed by 52.22%and 61.60%respectively,and reduces the mid-term voltage fluctuation amplitude by 15%and 30%,respectively.

关 键 词：太阳能电池 局部遮荫 特性曲线 MPPT 粒子群 差分进化 个体排序 粒子适应值 全局最大功率点 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程] TM615[自动化与计算机技术—控制科学与工程]