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Open AccessFeature PaperArticle

Day-Ahead vs. Intraday—Forecasting the Price Spread to Maximize Economic Benefits

1
Department of Operations Research, Faculty of Computer Science and Management, Wrocław University of Science and Technology, 50-370 Wrocław, Poland
2
Faculty of Pure and Applied Mathematics, Wrocław University of Science and Technology, 50-370 Wrocław, Poland
*
Author to whom correspondence should be addressed.
Energies 2019, 12(4), 631; https://doi.org/10.3390/en12040631
Received: 28 January 2019 / Revised: 9 February 2019 / Accepted: 12 February 2019 / Published: 16 February 2019
(This article belongs to the Special Issue Modeling and Forecasting Intraday Electricity Markets)
Recently, a dynamic development of intermittent renewable energy sources (RES) has been observed. In order to allow for the adoption of trading contracts for unplanned events and changing weather conditions, the day-ahead markets have been complemented by intraday markets; in some countries, such as Poland, balancing markets are used for this purpose. This research focuses on a small RES generator, which has no market power and sells electricity through a larger trading company. The generator needs to decide, in advance, how much electricity is sold in the day-ahead market. The optimal decision of the generator on where to sell the production depends on the relation between prices in different markets. Unfortunately, when making the decision, the generator is not sure which market will offer a higher price. This article investigates the possible gains from utilizing forecasts of the price spread between the intraday/balancing and day-ahead markets in the decision process. It shows that the sign of the price spread can be successfully predicted with econometric models, such as ARX and probit. Moreover, our research demonstrates that the statistical measures of forecast accuracy, such as the percentage of correct sign classifications, do not necessarily coincide with economic benefits. View Full-Text
Keywords: electricity prices; electricity markets; price spread; forecasting; ARX model; Probit model electricity prices; electricity markets; price spread; forecasting; ARX model; Probit model
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Maciejowska, K.; Nitka, W.; Weron, T. Day-Ahead vs. Intraday—Forecasting the Price Spread to Maximize Economic Benefits. Energies 2019, 12, 631.

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