Electric load forecasting using support vector machines for robust regression

Authors:
Sonia De Cosmis;Renato De Leone;Erik Kropat;Silja Meyer-Nieberg;Stefan Pickl
Affiliations:
University of Camerino, Camerino, Italy;University of Camerino, Camerino, Italy;Universität der Bundeswehr München, Neubiberg, Germany;Universität der Bundeswehr München, Neubiberg, Germany;Universität der Bundeswehr München, Neubiberg, Germany
Venue:
Proceedings of the Emerging M&S Applications in Industry & Academia / Modeling and Humanities Symposium
Year:
2013

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Abstract

Load forecasting is at the core of nearly all decisions made in energy markets. The electricity load demand is influenced by numerous factors - ranging from weather conditions over seasonal effects to socio-economic influences. In this paper, we present first computational results using a linear approach supported by support vector machines for robust regression.