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

Jakub Nowotarski and Rafał Weron

Energy Economics, 2016, vol. 57, issue C, 228-235

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)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (58)

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Working Paper: On the importance of the long-term seasonal component in day-ahead electricity price forecasting (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:57:y:2016:i:c:p:228-235

DOI: 10.1016/j.eneco.2016.05.009

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