Forecasting system imbalance volumes in competitive electricity markets

被引：40

作者：

Garcia, MP ^{[1
]}

Kirschen, DS ^{[1
]}

机构：

[1] Univ Manchester, Dept Elect Engn & Elect, Manchester M60 1QD, Lancs, England

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 2006年 / 21卷 / 01期

关键词：

data mining; electricity markets; multidimensional forecasting; neural networks; time series;

D O I：

10.1109/TPWRS.2005.860924

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：

Forecasting in power systems has been made considerably more complex by the introduction of competitive electricity markets. Furthermore, new variables need to be predicted by various market participants. This paper shows how a new methodology that combines classical and data mining techniques can be used to forecast the system imbalance volume, a key variable for the system operator in the market of England and Wales under the New Electricity Trading Arrangements (NETA).

引用

页码：240 / 248

页数：9

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