Exponential smoothing approaches for prediction in real-time electricity markets

Tryggvi Jónsson, Pierre Pinson, Henrik Aalborg Nielsen, Henrik Madsen

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Abstract

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.
Original languageEnglish
JournalEnergies
Volume7
Issue number6
Pages (from-to)3710-3732
ISSN1996-1073
DOIs
Publication statusPublished - 2014

Bibliographical note

© 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).

Keywords

  • Real-time electricity markets
  • Classification
  • Non-stationarity
  • Moving average

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