局部阴影情况下一种基于改进BFOA的光伏阵列GMPPT策略研究
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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.
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.
引文
[1]刘慧文,王生铁,温素芳,等.光伏系统区段划分变步长MPPT算法设计[J].可再生能源,2018,36(8):1151-1157.
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[10]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):192-196.
[11]峁美琴,余世杰,苏建徽.带MPPT功能的光伏阵列matlab通用仿真模型[J].系统仿真学报, 2005,17(5):1248-1251.
[12] K M Passino. Biomimicry of bacterial foraging for distributed optimization and control[J].IEEE Control Systems Magazine,2002,22(3):52-67.
[13]李晓晗.基于细菌觅食算法的PID参数整定[D].兰州:甘肃农业大学,2018.
[14]张明锐,蒋利明,孙华,等.基于免疫细菌觅食算法的大容量光伏阵列GMPPT算法[J].中国电机工程学报,2016,36(1):104-111.
[15]冯宝成,苏建徽.部分遮挡条件下光伏组件的建模与仿真研究[J].电气传动,2011,41(7):61-64.
[2]武迪,许春雨,宋建成,等.基于β参数的混合控制策略光伏系统MPPT算法研究[J].可再生能源,2018,36(1):8-14.
[3]聂晓华,赖家俊.局部阴影情况下光伏阵列全局最大功率点跟踪控制方法综述[J].电网技术,2012,38(12):3280-3285.
[4] Jun Qi, Youbing Zhang, Yi Chen. Modeling and maximum power point tracking(MPPT)method for PV array under partial shade conditions[J].Renewable Energy,2014,66(1):337-345.
[5]王云平,李颖,阮新波.基于局部阴影情况下光伏阵列电流特性的最大功率点跟踪算法[J].电工技术学报,2016,31(14):201-218.
[6]胡飞鹏,周娟,耿乙文.局部阴影情况下光伏阵列的最大功率点跟踪研究[J].电气传动,2013,43(12):15-19.
[7] Villa L F L, Ho T P, Crebier J C, et al.A power electronics equalizer application for partially shaded photovoltaic modules[J].IEEE Transactions on Industrial Electronics,2013,60(3):1179-1190.
[8] 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,2012,27(8):3627-3638.
[9]李翔,陈启卷,饶宛,等.基于HPSO算法光伏并网逆变器MPPT技术研究[J].可再生能源,2018,36(11):1600-1604.
[10]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):192-196.
[11]峁美琴,余世杰,苏建徽.带MPPT功能的光伏阵列matlab通用仿真模型[J].系统仿真学报, 2005,17(5):1248-1251.
[12] K M Passino. Biomimicry of bacterial foraging for distributed optimization and control[J].IEEE Control Systems Magazine,2002,22(3):52-67.
[13]李晓晗.基于细菌觅食算法的PID参数整定[D].兰州:甘肃农业大学,2018.
[14]张明锐,蒋利明,孙华,等.基于免疫细菌觅食算法的大容量光伏阵列GMPPT算法[J].中国电机工程学报,2016,36(1):104-111.
[15]冯宝成,苏建徽.部分遮挡条件下光伏组件的建模与仿真研究[J].电气传动,2011,41(7):61-64.