Forecasting system imbalance volumes in competitive electricity markets

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).

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