Forecasting system imbalance volumes in competitive electricity markets

Maria P. Garcia; Daniel S. Kirschen

doi:10.1109/TPWRS.2005.860924

Forecasting system imbalance volumes in competitive electricity markets

Maria P. Garcia
, Daniel S. Kirschen

Research output: Contribution to journal › Article › peer-review

Abstract

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). © 2006 IEEE.

Original language	English
Pages (from-to)	240-248
Number of pages	8
Journal	IEEE Transactions on Power Systems
Volume	21
Issue number	1
DOIs	https://doi.org/10.1109/TPWRS.2005.860924
Publication status	Published - Feb 2006

Keywords

Data mining
Electricity markets
Multidimensional forecasting
Neural networks
Time series

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10.1109/TPWRS.2005.860924

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abstract = "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). {\textcopyright} 2006 IEEE.",

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AB - 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). © 2006 IEEE.

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KW - Electricity markets

KW - Multidimensional forecasting

KW - Neural networks

KW - Time series

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DO - 10.1109/TPWRS.2005.860924

M3 - Article

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JO - IEEE Transactions on Power Systems

JF - IEEE Transactions on Power Systems

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Forecasting system imbalance volumes in competitive electricity markets

Abstract

Keywords

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