On the importance of the long-term seasonal component in day-ahead electricity price forecasting

Jakub Nowotarski and Rafał Weron

No HSC/16/05, HSC Research Reports from Hugo Steinhaus Center, Wroclaw University of Science and Technology

Abstract: In day-ahead electricity price forecasting (EPF) the daily and weekly seasonalities are always taken into account, but the long-term seasonal component (LTSC) is believed to add unnecessary complexity to the already parameter-rich models and is generally ignored. Conducting an extensive empirical study involving state-of-the-art time series models we show that (i) decomposing a series of electricity prices into a LTSC and a stochastic component, (ii) modeling them independently and (iii) combining their forecasts can bring - contrary to a common belief - an accuracy gain compared to an approach in which a given time series model is calibrated to the prices themselves.

Keywords: Electricity spot price; Forecasting; Day-ahead market; Long-term seasonal component (search for similar items in EconPapers)
JEL-codes: C14 C22 C51 C53 Q47 (search for similar items in EconPapers)
Pages: 15 pages
Date: 2016-03-15
New Economics Papers: this item is included in nep-ene and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (57)

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Related works:
Journal Article: On the importance of the long-term seasonal component in day-ahead electricity price forecasting (2016)
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