Electricity price forecasting: A review of the state-of-the-art with a look into the future

被引:936
|
作者
Weron, Rafal [1 ]
机构
[1] Wroclaw Univ Technol, Inst Org & Management, PL-50370 Wroclaw, Poland
关键词
Electricity price forecasting; Day-ahead market; Seasonality; Autoregression; Neural network; Factor model; Forecast combination; Probabilistic forecast; REGIME-SWITCHING MODELS; ARTIFICIAL NEURAL-NETWORKS; CONFIDENCE-INTERVAL ESTIMATION; SUPPLY FUNCTION EQUILIBRIUM; SHORT-TERM; TIME-SERIES; SPOT-PRICES; WAVELET TRANSFORM; MARKET PRICE; DENSITY FORECASTS;
D O I
10.1016/j.ijforecast.2014.08.008
中图分类号
F [经济];
学科分类号
02 ;
摘要
A variety of methods and ideas have been tried for electricity price forecasting (EPF) over the last 15 years, with varying degrees of success. This review article aims to explain the complexity of available solutions, their strengths and weaknesses, and the opportunities and threats that the forecasting tools offer or that may be encountered. The paper also looks ahead and speculates on the directions EPF will or should take in the next decade or so. In particular, it postulates the need for objective comparative EPF studies involving (i) the same datasets, (ii) the same robust error evaluation procedures, and (iii) statistical testing of the significance of one model's outperformance of another. (C) 2014 The Author. Published by Elsevier B.V. on behalf of International Institute of Forecasters. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bY-nc-nd/3.0/).
引用
收藏
页码:1030 / 1081
页数:52
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