A semiparametric model for electricity spot prices

Raimund M. Kovacevic, David Wozabal

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

This article proposes a semiparametric single-index model for short-term forecasting day-ahead electricity prices. The approach captures the dependency of electricity prices on covariates, such as demand for electricity, amount of energy produced by intermittent sources, and weather-dependent variables. To obtain parsimonious models, principal component analysis is used for dimension reduction. The approach is tested on two data sets from different markets and its performance is analyzed in terms of fit, forecast quality, and computational efficiency. The results are encouraging, in that the proposed method leads to a good in-sample fit and performs well out-of-sample compared with four benchmark models, including a SARIMA model as well as a functional nonparametric regression approach recently proposed in the literature. © 2014 IIE.
Original languageEnglish
Pages (from-to)344-356
JournalIIE Transactions (Institute of Industrial Engineers)
Volume46
Issue number4
DOIs
Publication statusPublished - 1 Apr 2014
Externally publishedYes

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