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Forecasting Electric Power Consumption Using Subspace Algorithms
Karlstad University, Faculty of Technology and Science, Department of Physics and Electrical Engineering.
2007 (English)In: International Journal of Power and Energy Systems, ISSN 1078-3466, Vol. 27, no 4, 393-397 p.Article in journal (Refereed) Published
Abstract [en]

A new approach for electric power consumption forecasting that consists of using subspace identification techniques is presented in the paper. The new and powerful subspace identification techniques are introduced to the members of the power system engineering community who are not familiar with them, and it is shown that they can be an important tool in this area of electrical engineering. The usefulness of the techniques is illustrated on real data, and the identified models give reliable 24-h ahead predictions.

Place, publisher, year, edition, pages
2007. Vol. 27, no 4, 393-397 p.
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kau:diva-19396DOI: 10.2316/Journal.203.2007.4.203-3756OAI: oai:DiVA.org:kau-19396DiVA: diva2:593043
Available from: 2013-01-21 Created: 2013-01-21 Last updated: 2013-10-29Bibliographically approved

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