Stochastic noises have a great adverse effect on the prediction accuracy of electric power load. Modeling online\nand filtering real-time can effectively improve measurement accuracy. Firstly, pretreating and inspecting statistically\nthe electric power load data is essential to characterize the stochastic noise of electric power load. Then, set order\nfor the time series model by Akaike information criterion (AIC) rule and acquire model coefficients to establish\nARMA (2,1) model. Next, test the applicability of the established model. Finally, Kalman filter is adopted to process\nthe electric power load data. Simulation results of total variance demonstrate that stochastic noise is obviously\ndecreased after Kalman filtering based on ARMA (2,1) model. Besides, variance is reduced by two orders, and every\ncoefficient of stochastic noise is reduced by one order. The filter method based on time series model does reduce\nstochastic noise of electric power load, and increase measurement accuracy.
Loading....