A refined parametric model for short term load forecasting

被引:91
作者
Charlton, Nathaniel [1 ]
Singleton, Colin [1 ]
机构
[1] CountingLab Ltd, Reading, Berks, England
关键词
Electricity; Regression; Forecasting competitions; Combining forecasts; Demand forecasting;
D O I
10.1016/j.ijforecast.2013.07.003
中图分类号
F [经济];
学科分类号
02 ;
摘要
We present a refined parametric model for forecasting electricity demand which performed particularly well in the recent Global Energy Forecasting Competition (GEFCom 2012). We begin by motivating and presenting a simple parametric model, treating the electricity demand as a function of the temperature and day of the data. We then set out a series of refinements of the model, explaining the rationale for each, and using the competition scores to demonstrate that each successive refinement step increases the accuracy of the model's predictions. These refinements include combining models from multiple weather stations, removing outliers from the historical data, and special treatments of public holidays. (C) 2013 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:364 / 368
页数:5
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