A Load Forecasting Method for Distribution Networks Considering the Influence of Photovoltaics and Traditional Load

In order to address the impact of uncertainty in distributed photovoltaics on distribution network load forecasting, this paper proposes a distribution network load forecasting method that considers the impact of photovoltaics and traditional loads. Screen sample data for comprehensive load density indicators through grey correlation analysis. Calculate the correlation degree between the sample data and the load density index of the area to be predicted, and select the training data of the LS-SVM model based on the correlation degree as the standard for load density prediction. Taking the distribution network load data of a certain region for the past year as an example, compared with traditional technical solutions, the results show that the proposed method has significant advantages in load forecasting accuracy, error rate, stability, and economic benefits.