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

被引：74
作者：
Pousinho, H. M. I. [1 ,2 ]
Mendes, V. M. F. [3 ]
Catalao, J. P. S. [1 ,2 ]
机构：
[1] Univ Beira Interior, Dept Electromech Engn, P-6201001 Covilha, Portugal
[2] Univ Tecn Lisboa, Inst Super Tecn, Ctr Innovat Elect & Energy Engn, P-1049001 Lisbon, Portugal
[3] Inst Super Engn Lisboa, Dept Area Elect Engn & Automat, P-1950062 Lisbon, Portugal
来源：
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS | 2012年 / 39卷 / 01期
关键词：
Electricity market; Price forecasting; Swarm optimization; Neural networks; Fuzzy logic; NEURAL-NETWORK; MODELS;
D O I：
10.1016/j.ijepes.2012.01.001
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. 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, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码：29 / 35
页数：7
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