An ARMA Cooperate with Artificial Neural Network Approach in Short-Term Load Forecasting

Short-term load forecasting is important for electricity load planning and dispatches the loading of generating units in order to meet the electricity system demand. The precision of the load forecasting is related to electricity company's economic. This paper presents a approach named an autoregressive moving average (ARMA) cooperate with BP Artificial Neural Network (BPNN) approach, which can combine the linear component and nonlinear component at the same time. the experiment result shows that the MAPE of this method is 0.92%, and MSE is 17.07, compared to single ARMA's MAPE 2.08% and MSE 47.65 or BPNN's MAPE 2.63% and MSE 56.91, this method is outperform the single ARMA and BPNN forecast method.