Evaluating prediction models for electricity consumption

  • Lasse A. Karlsen Faculty of Engineering and Science, University of Agder
  • Morten Goodwin Faculty of Engineering and Science, University of Agder Teknova AS, Grimstad, Norway

Abstract

This paper presents a system for visualizing electricity consumption
data along with the implementation of a pattern recognition approach for peak
prediction. Various classification algorithms and machine learning techniques are
tested and discussed; in particular, Support Vector Machine (SVM), Gaussian
Mixture Model (GMM) and hierarchical classifiers. Most notably, the best
algorithms are able to detect 70% of the peaks occurring within the next 24 hours.
Also, various ways of correlating energy consumption are considered in the present
context. Finally, a few directions for future work are discussed.

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Artikler