%Aigaion2 BibTeX export von HES SO Valais Publications
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@INPROCEEDINGS{,
        author = {Dufour, Luc and Genoud, Dominique and Rizzo, Gianluca and Ladevie, Bruno and Bezian, Jean-Jacques},
      keywords = {Advanced Metering Infrastructure, Data intelligence analysis, Energy information management, Microgrid},
         month = aug,
         title = {Identification method for home electrical signal disaggregation},
          year = {2014},
     publisher = {The 13th International Conference on Sustainable Energy Technologies},
      location = {Geneva, Switzerland},
  organization = {SET 2014, 25-28.08.2014},
      abstract = {In order to enable demand response schemes for residential and industrial users, it is crucial to be able to predict and monitor
each component of the total power consumption of a household or of an industrial site over time. We used the cross-validation
method which is a model validation technique for assessing how the results of a statistical analysis will generalize to an
independent data set. It is mainly used in settings where the goal is prediction, and one wants to estimate how accurately a
predictive model will perform in practice. We exploit Non-Intrusive Load Monitoring (NILM) techniques in order to provide
behavior patterns of the variables identified. This work presents a review Non-Intrusive Load Monitoring (NILM) techniques
and describe the results of recognition patterns used for the identification of electrical devices.The proposed method has been
validated on an experimental setting and using direct measurements of appliances consumption, proving that it allows achieving
a high level of accuracy in load disaggregation.}
}