Application of Support Vector Regression and Time Series Method in Short-term Power Load Forecasting with Regional Difference

Aims: The aim of this study is to perform short-term load forecasting. Background: Short-term load forecasting plays a key role in power dispatching. It provides basic data for basic power generation planning and system safety analysis so that the power dispatching work is more practical and the power generation efficiency is higher. Objective: The aim of this study is to ensure the safe operation of the electricity market and relieve the pressure of supply and demand. Method: In this paper, the SVR model is used for short-term load prediction. Results: The SVR model has the advantage of minimizing the structural risk and has good generalization performance for the predicted object. At the same time, the global optimization is ensured, a lot of mapping calculation is reduced, the actual risk is reduced, and the prediction performance is improved. Conclusion: The target model has higher forecasting accuracy than other forecasting models and can effectively solve the problems of the power market.