Electricity price forecasting in deregulated markets: A review and evaluation

被引：323

作者：

Aggarwal, Sanjeev Kumar ^{[1
]}

Saini, Lalit Mohan ^{[1
]}

Kumar, Ashwani ^{[1
]}

机构：

[1] Natl Inst Technol, Dept Elect Engn, Kurukshetra, Haryana, India

来源：

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS | 2009年 / 31卷 / 01期

关键词：

Price forecasting; Stochastic time series; Regression models; Neural networks; Deregulated markets; CONFIDENCE-INTERVAL ESTIMATION; WAVELET TRANSFORM; NEURAL-NETWORKS; MARGINAL PRICE; PREDICTION; LOADS; HOUR;

D O I：

10.1016/j.ijepes.2008.09.003

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：

The main methodologies used in electricity price forecasting have been reviewed in this paper. The following price-forecasting techniques have been covered: (i) stochastic time series, (ii) causal models, and (iii) artificial intelligence based models. The quantitative analysis of the work done by various authors has been presented based on (a) time horizon for prediction, (b) input variables, (c) output variables, (d) results, (e) data points used for analysis, (f) preprocessing technique employed, and (g) architecture of the model. The results have been presented in the form of tables for ease of comparison. Classification of various price-influencing factors used by different researchers has been done and put for reference. Application of various models as applied to different electricity markets is also presented for consideration. (C) 2008 Elsevier Ltd. All rights reserved.

引用

页码：13 / 22

页数：10

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