Short-Term Load Forecasting of Power System Based on Support Vector Machine Theory

Abstract

The short-term load forecasting of the power system is an important basis for the safe and economical operation of the power system. With the introduction of the price competition mechanism into the power system to form the power market, higher requirements are put forward for the accuracy and response speed of short-term load forecasting. The key problem of power system load forecasting is to establish a corresponding mathematical model according to the historical data of the forecast object to describe its development law. Support vector machine theory (SVM) can better solve practical problems such as small samples, nonlinearity, high dimensionality and local minima, and can be used to establish a relatively complete load forecasting model. The research shows that the application of SVM for load forecasting of power system has the advantages of high accuracy and fast speed, which significantly improves the effect of load forecasting.