Prediction of Electric Power Consumption Based on the Improved GM(1, 1)

Zhengren Wu, Mei Liu, Xin Wang


Based on the electric power consumption data in 2001-2010, this paper discusses GM (1, 1) model and its improved model in the application of power consumption forecasting. Due to the traditional Grey Model itself has certain defects, we grouped the original sequence according to the degree of deviation first, and then combined with nonlinear GM (1, 1, α) to improve the traditional GM (1, 1) model. Through the relative error testing and the posterior testing, this paper made a comparative analysis to the traditional GM (1, 1) model and the improved GM. Example of Beijing shows that the improved model had good accuracy; it had a good application value in the actual prediction system.




Grey Model group nonlinear; GM (1, 1, α); Posterior testing Electric Power Consumption

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