GM (1,1) model application in power load forecasting based on moving average method

Grey prediction has advantages of need less historical data, foperating speed is fast, algorithm is simple, easy to test, so it is suitable for use in power load forecasting. But grey model has some limitations, the data dispersion degree is more bigger, the gray is also more bigger, it will reduce the accuracy of prediction. This paper adopts the moving average method to improve the raw data, so as to increase the data weights, while avoiding predicted value excessive volatility, So it can improve the load forecast accuracy.