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Energies 2014, 7(6), 3710-3732; doi:10.3390/en7063710

Exponential Smoothing Approaches for Prediction in Real-Time Electricity Markets

3,* , 2
1 Department of Applied Mathematics,Technical University of Denmark, Matematiktorvet 303, 2800 Kgs. Lyngby, Denmark 2 ENFOR A/S, Lyngsø Allé 3, 2970 Hørsholm, Denmark 3 Department of Electrical Engineering, Technical University of Denmark, Elektrovej 325,2800 Kgs. Lyngby, Denmark
* Author to whom correspondence should be addressed.
Received: 31 March 2014 / Revised: 31 May 2014 / Accepted: 6 June 2014 / Published: 16 June 2014
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The optimal design of offering strategies for wind power producers is commonly based on unconditional (and, hence, constant) expectation values for prices in real-time markets, directly defining their loss function in a stochastic optimization framework. This is why it may certainly be advantageous to account for the seasonal and dynamic behavior of such prices, hence translating to time-varying loss functions. With that objective in mind, forecasting approaches relying on simple models that accommodate the seasonal and dynamic nature of real-time prices are derived and analyzed. These are all based on the well-known Holt–Winters model with a daily seasonal cycle, either in its conventional form or conditioned upon exogenous variables, such as: (i) day-ahead price; (ii) system load; and (iii) wind power penetration. The superiority of the proposed approach over a number of common benchmarks is subsequently demonstrated through an empirical investigation for the Nord Pool, mimicking practical forecasting for a three-year period over 2008–2011.
Keywords: real-time electricity markets; classification; non-stationarity; moving average real-time electricity markets; classification; non-stationarity; moving average
This is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Jónsson, T.; Pinson, P.; Nielsen, H.A.; Madsen, H. Exponential Smoothing Approaches for Prediction in Real-Time Electricity Markets. Energies 2014, 7, 3710-3732.

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