论文信息 - An Improved Combined Forecasting Method for Electric Power Load Based on Autoregressive Integrated Moving Average Model

An Improved Combined Forecasting Method for Electric Power Load Based on Autoregressive Integrated Moving Average Model

Daily power load forecasting is an essential function in electrical power system operation and planning. The accuracy peak power load forecasting can ensure secure operation of the electric utility grid and have the least cost. Therefore, a good deal of forecasting methods have been proposed and studied in this domain. In this paper, Autoregressive Integrated Moving Average (ARIMA) model is developed to forecast short-term power load of New South Wales in Australia, then rectify residual errors using method of weighted mean. This combined method makes accuracy higher than the single ARIMA model.

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