Smart Grid Inspired Future Technologies. Second EAI International Conference, SmartGIFT 2017, London, UK, March 27–28, 2017, Proceedings

Research Article

Deep Learning Based Consumer Classification for Smart Grid

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  • @INPROCEEDINGS{10.1007/978-3-319-61813-5_13,
        author={K\^{a}lm\^{a}n Tornai and Andr\^{a}s Ol\^{a}h and Rajmund Drenyovszki and L\^{o}r\^{a}nt Kov\^{a}cs and Istv\^{a}n Pint\^{e}r and J\^{a}nos Levendovszky},
        title={Deep Learning Based Consumer Classification for Smart Grid},
        proceedings={Smart Grid Inspired Future Technologies. Second EAI International Conference, SmartGIFT 2017, London, UK, March 27--28, 2017, Proceedings},
        proceedings_a={SMARTGIFT},
        year={2017},
        month={9},
        keywords={Classification methods Consumer classification Deep learning Softmax layer network},
        doi={10.1007/978-3-319-61813-5_13}
    }
    
  • Kálmán Tornai
    András Oláh
    Rajmund Drenyovszki
    Lóránt Kovács
    István Pintér
    János Levendovszky
    Year: 2017
    Deep Learning Based Consumer Classification for Smart Grid
    SMARTGIFT
    Springer
    DOI: 10.1007/978-3-319-61813-5_13
Kálmán Tornai1,*, András Oláh1, Rajmund Drenyovszki2, Lóránt Kovács2, István Pintér2, János Levendovszky3
  • 1: Pázmány Péter Catholic University
  • 2: Pallas Athene University
  • 3: Budapest University of Technology and Economics
*Contact email: tornai.kalman@itk.ppke.hu

Abstract

Classification of different power consumers is a very important task in smart power transmission grids as the different type of consumers may be treated with different conditions. Furthermore, the power suppliers can use the category information of consumers to forecast better their behavior which is a relevant task for load balancing.