4.6 Article

An evaluation of methods for very short-term load forecasting using minute-by-minute British data

期刊

INTERNATIONAL JOURNAL OF FORECASTING
卷 24, 期 4, 页码 645-658

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ELSEVIER
DOI: 10.1016/j.ijforecast.2008.07.007

关键词

Electricity demand; Very short-term; Exponential smoothing; Combining

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This paper uses minute-by-minute British electricity demand generation. We observations to evaluate methods for prediction between 10 and 30 minutes ahead. Such very short lead times are important for the real-time scheduling of electricity consider methods designed to capture both the intraday and the intraweek seasonal cycles in the data, including ARIMA modelling, an adaptation of Holt-Winters' exponential smoothing, and a recently proposed exponential smoothing method that focuses on the evolution of the intraday cycle. We also consider methods that do not attempt to model the seasonality, as well as an approach based on weather forecasts. For very short-term prediction, the best results were achieved using the Holt-Winters, adaptation and the new intraday cycle exponential smoothing method. Looking beyond the very short-term, we found that combining the method based on weather forecasts with the Holt-Winters' adaptation resulted in forecasts that outperformed all other methods beyond about an hour ahead. (C) 2008 International Institute of Forecasters. Published by Elsevier B.V All rights reserved.

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