Power System Short Term Load Forecasting Based on Weather Factors

Aiming at the shortcomings of traditional load forecasting strategy, this paper considers the comprehensive application of various meteorological factors in load forecasting, and it proposes a power system short term load forecasting method based on the least squares support vector machine (LSSVM) model. Firstly, it provides a theoretical basis for selecting modeling variables by correlation analysis, and deals with the load data to optimize the sample quality by similarity principle. Secondly, it establishes a weather LSSVM load forecasting model, and the model is trained and tested by historical load data of a certain region. Finally, the accuracy and validity of the prediction model are verified by simulation.