光伏发电性能物理预测模型的研究

Research of photovoltaic prediction model

为提高光伏发电预测的精度,通过两种不同温度和光强下的电池短路电流、开路电压以及最大功率点处电流和电压电性参量,建立任意温度和光强下光伏发电预测模型。结果表明:在光强不变温度改变的条件下,电流电压全局拟合均方根误差不超过1.443 9 mA,预测最大输出功率的相对误差最大为10.61%;在光强改变温度不变的条件下,电流电压全局拟合均方根误差不超过0.982 1 mA;预测最大输出功率的相对误差最大为6.21%;总体来说,模型能正确预测光伏电池的输出特性,满足工程应用要求,且多晶硅的预测难度大于单晶与非晶硅电池。

In order to improve the forecasting accuracy of photovoltaic power generation, a new model based on cells' short circuit current, open circuit voltage under two different temperatures and light intensities with current and voltage at maximum power point was proposed. The model was used to predict the cell output power under random temperature and light intensity. The results indicate that the mean square root error is not more than 1.443 9 mA on the condition of changed temperature and constant light intensity. The mean square root error is not more than 0.9821 mA on the condition of changed light intensity and constant temperature. It's found that the prediction of polysilicon cell is harder than the other two kinds of silicon cells(monocrystalline and amorphous crystalline silicon cells).Overall, the model can predict the output characteristics of photovoltaic cells and satisfy the requirement of engineering application.