摘要
局部阴影情况下光伏阵列输出特性的P-U曲线呈多峰形,I-U曲线呈多膝形。利用传统跟踪方法跟踪全局最大功率点时会陷入局部峰值点。文章针对细菌觅食算法(BFOA)在全局范围内收敛速度较慢的不足,提出一种改进BFOA。该改进算法首先在阴影遮挡发生时判断阴影情况,然后设法缩减电压跟踪范围,并在重新确定的电压范围内跟踪全局的最大功率点。文章在Matlab/Simulink环境中搭建光伏阵列,并将改进BFOA的模拟结果与传统扰动观察法、常规BFOA的模拟结果进行对比。研究结果表明:改进BFOA能够在局部阴影条件下成功地跟踪到全局最大功率点,且跟踪过程的动态响应时间明显缩短。
In the partial shadow, the output characteristics of the photovoltaic(PV) array in partial shadow are expressed in two aspects. The P-U curve will be multi-peak and the I-U curve will be multi-knee. Tracking the global maximum power point(GMPP) in traditional method will mistakenly choose the local peak point. An improved method based on bacterial foraging optimization algorithm(BFOA) is proposed, in order to solve the problem that the BFOA converges slowly in the global range. The improved algorithm first determines the shadow condition when shadow occurs, and then tries to decrease the voltage tracking range and track the GMPP in the newly determined voltage range. The PV array and algorithm model are built in Matlab/Simulink environment, and the simulation results are compared with that of traditional perturb and observe algorithm(P&O) and conventional BFOA;The simulation results show that the proposed improved BFOA can well track GMPP in partial shadow, and the dynamic response time is significantly shortened during the tracking process.
作者
李恒瑞
廖冬初
陈俊
Li Hengrui;Liao Dongchu;Chen Jun(School of Electrical and Electronic Engineering,Hubei University of Technology,Wuhan 430068,China)
出处
《可再生能源》
CAS
北大核心
2019年第4期513-520,共8页
Renewable Energy Resources
基金
湖北省重点实验室面上项目(HBSEES201710)
