基于主成分回归分析的气象因子对光伏发电量的影响

INFLUENCE OF METEOROLOGICAL FACTORS ON PHOTOVOLTAIC POWER GENERATION BASED ON PRINCIPAL COMPONENT REGRESSION ANALYSIS

采用主成分分析方法降低气象维度,提取互不相关的综合性评价指标,并将提取出的主要成分作为回归模型的自变量建立多元线性回归模型。通过检验可知:主成分回归模型的拟合优度优于直接回归模型,提高了预测精度,预测结果也较为稳定。因此,主成分分析法可有效提高光伏发电量的预测精度。

This article uses principal component analysis to reduce the meteorological dimension,extracts comprehensive evaluation indicators that are not related to each other,and uses the extracted main components as independent variables of the regression model to establish a multiple linear regression model.By verification,it is found that the goodness of fit of the principal component regression model is better than that of the direct regression model,which improves the prediction accuracy and the prediction results are more stable.Therefore,the principal component analysis method can effectively improve the prediction accuracy of photovoltaic power generation.