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This paper proposes a novel technique to forecast day-ahead electricity prices based on Panel Cointegration (PC). The current researches on the electricity price forecasting focus on the analysis of unstable economic time series. However, due to the difference of the allocation of power resource and consumption in different regions, the time series of electricity consumption and sales price in a single...
Demand response is a reduction in the consumption of electricity by customers from their expected consumption in response to reliability or price triggered signals. Enabled by advanced metering infrastructure and other smart grid technologies, it is expected to be a crucial mechanism to compensate system uncertainties and the associated risks including those related to intermittent renewable generation...
In this paper, issues related to price forecasting in a smart grid environment are discussed. In such an environment, demand-side resources are enabled to play a bigger role in the operation of electricity markets, compared to the limited demand-side market participation in most of the existing markets. The response of the demand-side to price forecasts could impact the formation of price patterns,...
This paper presents a forecasting technique to predict next-day electricity spot prices and volatilities. Our technique combines a fundamental model formulated as supply stack modeling, with an econometric analysis based on the GARCH methodology. Empirical results from the wholesale electricity market of Great Britain are discussed.
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