屠亚南, 于艾清. 基于平抛模型的光伏多峰最大功率点预测跟踪方法[J]. 现代电力, 2019, 36(3): 27-33.
引用本文: 屠亚南, 于艾清. 基于平抛模型的光伏多峰最大功率点预测跟踪方法[J]. 现代电力, 2019, 36(3): 27-33.
TU Yanan, YU Aiqing. Photovoltaic Multi-peak Maximum Power Point Predictive Tracking Method Based on Flat Parabolic Model[J]. Modern Electric Power, 2019, 36(3): 27-33.
Citation: TU Yanan, YU Aiqing. Photovoltaic Multi-peak Maximum Power Point Predictive Tracking Method Based on Flat Parabolic Model[J]. Modern Electric Power, 2019, 36(3): 27-33.

基于平抛模型的光伏多峰最大功率点预测跟踪方法

Photovoltaic Multi-peak Maximum Power Point Predictive Tracking Method Based on Flat Parabolic Model

  • 摘要: 局部阴影条件下,现有的常规光伏电池模型不再适用。结合光伏阵列电流压特性曲线和质点平抛运动轨迹的相似性,构建了适用于阴影条件下的光伏阵列运动学平抛模型,并利用改进粒子群算法对其求解进行最大功率预测。由于平抛模型是对光伏阵列电流电压特性曲线的拟合,而拟合曲线不一定精确,单独使用该模型预估追踪最大功率点存在误差。针对上述问题,在使用改进PSO算法预测光伏阵列的最大功率点后,再利用指数变步长电导增量法进行局部跟踪。在MATLAB中通过不同运行工况下的仿真实验,验证了此多峰寻优方法的可行性,该方法能够有效缩短寻优时间,且减少寻优时系统的振荡,从而达到提高收敛速度和光伏发电效率的目的。

     

    Abstract: Existing photovoltaic cell models are no longer applicable under partial shading conditions. In this paper, based on the similarity between the current-voltage characteristic curve of photovoltaic arrays and the particle flat parabolic motion trajectory, a kinetic flat parabolic model for photovoltaic arrays under shaded conditions is built and is solved by the improved particle swarm algorithm to obtain the maximum power prediction. Because the flat parabolic model only fits the current-voltage characteristic curve of photovoltaic arrays, there are errors when the model is used alone to predict the maximum power point. To deal with the above problem, an index variable step conductor increment method is used to track the maximum power point after estimating it by the flat parabolic model. The multi-peak optimization method is validated by the simulation results under different operating conditions in MATLAB. This method can effectively reduce the optimization time and reduce the oscillation during optimizing process. The convergence speed and photovoltaic generation efficiency can be increased.

     

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