DocumentCode
2616082
Title
Forecasting system imbalance volumes in competitive electricity markets
Author
Garcia, M.P. ; Kirschen, D.S.
Author_Institution
Univ. of Manchester Inst. of Sci. & Technol., UK
fYear
2004
fDate
10-13 Oct. 2004
Firstpage
1805
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).
Keywords
data mining; load forecasting; neural nets; power markets; power system analysis computing; time series; England market; New Electricity Trading Arrangement; Wales market; data mining; electricity market; neural network; power system forecasting; time series; Data mining; Economic forecasting; Electricity supply industry; Industrial power systems; Load forecasting; Multidimensional systems; Neural networks; Power markets; Power systems; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Systems Conference and Exposition, 2004. IEEE PES
Print_ISBN
0-7803-8718-X
Type
conf
DOI
10.1109/PSCE.2004.1397617
Filename
1397617
Link To Document