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Statistics-Based Approach to Enable Consumer Profile Definition for Demand Response Programs

  • Conference paper
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Distributed Computing and Artificial Intelligence, 14th International Conference (DCAI 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 620))

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Abstract

This paper presents a statistical analysis of a database generated by voltage and current measurements acquired in a laboratorial environment, which simulates a residential kitchen. In this sense, data were acquired during one month in order to verify both the occurrence of errors as well as the possible identification of the loads. Thus, it is intended that the statistical analysis allows the database to be used to the purposes of Demand Response. However, at first, there was an analysis by histograms in order to verify the occurrence of errors on the measurements and then the feature extraction stage. In the sequence, these features were used to dene decision rules that could perform the identification of loads. The results obtained demonstrated an average precision rate of more than 90%.

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References

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Acknowledgements

This paper was supported by FAPESP (grant number 2016/00641–4), CAPES and CNPq.

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Authors and Affiliations

  1. Department of Electrical Engineering, Federal University of Sao Carlos - UFSCar, Sao Carlos, Brazil

    R. A. S. Fernandes & L. O. Deus

  2. Knowledge Engineering and Decision Support Research Center – GECAD, Institute Polytechnic of Porto – IPP, Porto, Portugal

    L. Gomes & Z. Vale

Authors
  1. R. A. S. Fernandes
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  2. L. O. Deus
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  3. L. Gomes
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  4. Z. Vale
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Corresponding author

Correspondence to R. A. S. Fernandes .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, Department of Electronics, Information and Communication Engineering , Osaka Institute of Technology, Osaka, Osaka, Japan

    Sigeru Omatu

  2. Departamento de Informática y Automática, Facultad de Ciencias, Universidad de Salamanca , Salamanca, Spain

    Sara Rodríguez

  3. Departamento de Informática y Automática, Facultad de Ciencias, Universidad de Salamanca, Salamanca, Spain

    Gabriel Villarrubia

  4. GECAD - Instituto Superior de Engenharia, Porto, Portugal

    Pedro Faria

  5. Department of Control and Management Systems, Kielce University of Technology, Faculty of Electrical Engineering and Computer Science, Kielce, Poland

    Paweł Sitek

  6. Departamento de Informática y Automática, Universidad de Salamanca, Salamanca, Spain

    Javier Prieto

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Fernandes, R.A.S., Deus, L.O., Gomes, L., Vale, Z. (2018). Statistics-Based Approach to Enable Consumer Profile Definition for Demand Response Programs. In: Omatu, S., Rodríguez, S., Villarrubia, G., Faria, P., Sitek, P., Prieto, J. (eds) Distributed Computing and Artificial Intelligence, 14th International Conference. DCAI 2017. Advances in Intelligent Systems and Computing, vol 620. Springer, Cham. https://doi.org/10.1007/978-3-319-62410-5_8

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  • DOI: https://doi.org/10.1007/978-3-319-62410-5_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62409-9

  • Online ISBN: 978-3-319-62410-5

  • eBook Packages: EngineeringEngineering (R0)

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