Application of a new hybrid neuro-evolutionary system for day-ahead price forecasting of electricity markets

被引：38

作者：

Amjady, Nima ^{[1
]}

Keynia, Farshid ^{[1
]}

机构：

[1] Semnan Univ, Dept Elect Engn, Semnan, Iran

来源：

APPLIED SOFT COMPUTING | 2010年 / 10卷 / 03期

关键词：

Hybrid neuro-evolutionary system; Neural network; Evolutionary algorithm; Price forecast; CONFIDENCE-INTERVAL ESTIMATION; ARIMA MODELS; NETWORK; PREDICTION; INFORMATION;

D O I：

10.1016/j.asoc.2009.09.008

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a new forecast strategy is proposed for day-ahead prediction of electricity prices, which are so valuable for both producers and consumers in the new competitive electric power markets. However, electricity price has a nonlinear, volatile and time dependent behavior owning many outliers. Our forecast strategy is composed of a preprocessor and a Hybrid Neuro-Evolutionary System (HNES). Preprocessor selects the input features of the HNES according to MRMR ( Maximum Relevance Minimum Redundancy) principal. The HNES is composed of three Neural Networks (NN) and Evolutionary Algorithms ( EA) in a cascaded structure with a new data flow among its building blocks. The effectiveness of the whole proposed method is demonstrated by means of real data of the PJM and Spanish electricity markets. Also, the proposed price forecast strategy is compared with some of the most recent techniques in the area. (C) 2009 Elsevier B. V. All rights reserved.

引用

页码：784 / 792

页数：9

共 33 条

[11] A solution to the unit-commitment problem using integer-coded genetic algorithm [J].

Damousis, IG ;

Bakirtzis, AG ;

Dokopoulos, PS .

IEEE TRANSACTIONS ON POWER SYSTEMS, 2004, 19 (02) :1165-1172

[12]

DANFORESEE F, 1997, INT C NEUR NETW, V3, P1930

[13] Reliability and price risk assessment of a restructured power system with hybrid market structure [J].

Ding, Y ;

Wang, P .

IEEE TRANSACTIONS ON POWER SYSTEMS, 2006, 21 (01) :108-116

[14]

Fausett L., 1994, Fundamentals of neural networks: architectures, algorithms, and applications

[15] Generation scheduling in a deregulated system. The Norwegian case - Discussion [J].

Fotuhi-Firuzabad, M ;

Billinton, R .

IEEE TRANSACTIONS ON POWER SYSTEMS, 1999, 14 (01) :81-81

[16] Forecasting system imbalance volumes in competitive electricity markets [J].

Garcia, MP ;

Kirschen, DS .

IEEE TRANSACTIONS ON POWER SYSTEMS, 2006, 21 (01) :240-248

[17] A GARCH forecasting model to predict day-ahead electricity prices [J].

Garcia, RC ;

Contreras, J ;

van Akkeren, M ;

Garcia, JBC .

IEEE TRANSACTIONS ON POWER SYSTEMS, 2005, 20 (02) :867-874

[18] Modeling and forecasting electricity prices with input/output hidden Markov models [J].

González, AM ;

San Roque, AM ;

García-González, J .

IEEE TRANSACTIONS ON POWER SYSTEMS, 2005, 20 (01) :13-24

[19] Improving market clearing price prediction by using a committee machine of neural networks [J].

Guo, JJ ;

Luh, PB .

IEEE TRANSACTIONS ON POWER SYSTEMS, 2004, 19 (04) :1867-1876

[20] Day-ahead electricity price forecasting in a grid environment [J].

Li, Guang ;

Liu, Chen-Ching ;

Mattson, Chris ;

Lawarree, Jacques .

IEEE TRANSACTIONS ON POWER SYSTEMS, 2007, 22 (01) :266-274

← 1 2 3 4 →