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Evaluation of classification methodologies and Features selection from smart meter data
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0003-4589-7045
2017 (English)In: Energy Procedia, Elsevier Ltd , 2017, p. 2250-2256Conference paper, Published paper (Refereed)
Abstract [en]

The choice of the classification algorithm to map the feature vector to a known labelled database signature is an important step toward loads identification in non-intrusive load monitoring NILM. In this paper, we investigate the quality of load recognition when using various smart features and the commonly used classification algorithms. A low error rate is observed when using classification tree DT, k-NN and support vector machine SVM classifier, the error rate ranges between 20 % and 29 %. Among the smart meter features, the current waveform, the active/reactive power and the transient features have higher interesting recognition results when associated with a specific classifier.

Place, publisher, year, edition, pages
Elsevier Ltd , 2017. p. 2250-2256
Keywords [en]
Feature selection, Loads recognition, NILM, Smart meter, Feature extraction, Image retrieval, Nearest neighbor search, Smart meters, Support vector machines, Classification algorithm, Classification methodologies, Classification trees, Features selection, Loads identification, Nonintrusive load monitoring, Transient features, Classification (of information)
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-42442DOI: 10.1016/j.egypro.2017.12.626ISI: 000452901602063Scopus ID: 2-s2.0-85041530100OAI: oai:DiVA.org:mdh-42442DiVA, id: diva2:1282690
Conference
9th International Conference on Applied Energy, ICAE 2017, 21 August 2017 through 24 August 2017
Available from: 2019-01-25 Created: 2019-01-25 Last updated: 2019-03-29Bibliographically approved

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Maher, AzazaWallin, Fredrik

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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
  • html
  • text
  • asciidoc
  • rtf