industrial user short-term load prediction method based on morphological clustering and LightGBM

The invention provides an industrial user short-term load prediction method based on morphological clustering and LightGBM, and relates to the technical field of power system load prediction. The method comprises the following steps: firstly, clustering acquired industrial user load data by utilizing an industrial user morphological clustering algorithm; Performing characteristic engineering processing according to the load characteristics of each type of users after morphological clustering; Then, training and predicting various types of load data subjected to morphological clustering and corresponding feature engineering processing by using a corresponding LightGBM model; And finally, carrying out model fusion on the LightGBM model prediction results of various users to obtain a final prediction result. According to the industrial user short-term load prediction method based on morphological clustering and LightGBM provided by the invention, the characteristic that different industrial users have different