Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

被引：47
|
作者：
Catalao, J. P. S. [1 ,2 ]
Pousinho, H. M. I. [1 ]
Mendes, V. M. F. [3 ]
机构：
[1] Univ Beira Interior, Dept Electromech Engn, P-6201001 Covilha, Portugal
[2] Univ Tecn Lisbon, Ctr Innovat Elect & Energy Engn, Inst Super Tecn, P-1049001 Lisbon, Portugal
[3] Inst Super Engn Lisboa, Dept Elect Engn & Automat, P-1950062 Lisbon, Portugal
来源：
ENERGY CONVERSION AND MANAGEMENT | 2011年 / 52卷 / 02期
关键词：
Electricity market; Fuzzy logic; Neural networks; Price forecasting; Wavelet transform; NEURO-EVOLUTIONARY ALGORITHM; WAVELET TRANSFORM; ARIMA MODELS; NETWORK; SYSTEM; ENVIRONMENT; ANFIS;
D O I：
10.1016/j.enconman.2010.08.035
中图分类号：
O414.1 [热力学];
学科分类号：
摘要：
In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码：1061 / 1065
页数：5
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