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Title: Mid-term electricity price forecasting using future data Authors:  Rick Steinert - European University Viadrina (Germany)
Florian Ziel - University of Duisburg-Essen (Germany) [presenting]
Abstract: Due to the liberalization of markets, the change in the energy mix and the surrounding energy laws, electricity research is a dynamically altering field with steadily changing challenges. One challenge is to provide reliable mid-term forecasts despite high variation in the time series of electricity prices. This issue is tackled in a promising and novel approach. By utilizing the high precision of econometric autoregressive models and the expectations of market participants reflected in future prices, we show that the forecasting performance can be vastly increased while maintaining hourly precision. We investigate the day-ahead electricity price of the EPEX Spot for Germany and Austria and setup a model which incorporates the Phelix future of the EEX for Germany and Austria. The model can be considered as an AR24-X model with one distinct model for each hour of the day. We are able to show that future data contains relevant price information for future time periods of the day-ahead electricity price. By implementing a fast and efficient lasso estimation approach we demonstrate that our model can outperform several other models of the literature.