Advertisement

An Innovator Nonintrusive Method for Disaggregating and Identifying Two Simultaneous Household Loads

  • Máximo Pérez-Romero
  • Enrique Romero-Cadaval
  • Adolfo Lozano-Tello
  • João Martins
  • Rui Lopes
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 423)

Abstract

At the present time the monitoring systems are important in some areas, such as electric power supply industry and household environment because they provide useful information to energy storage and management tasks. A new nonintrusive monitoring method is proposed in this paper and it is able to disaggregate and identify two loads working simultaneously using a single measuring sensor and a least squares regression algorithm based on discrete form of the S-Transform.

Keywords

Monitoring nonintrusive disaggregation identifying simultaneously S-Transform 

References

  1. 1.
  2. 2.
    Gregor, R., Simon, F., Ulf, J.J., Hahnel, P.B., Bernhard, W.-H.: What the term Agent stands for in the Smart Grid Definition of Agents and Multi-Agent Systems from an Engineer’s Perspective. In: Proceedings of the Federated Conference on Computer Science and Information Systems, Wroclaw, Poland, pp. 1301–1305 (2012)Google Scholar
  3. 3.
    Hart, G.W.: Nonintrusive Appliance Load Monitoring. Proceedings of the IEEE, 1870–1891 (1992)Google Scholar
  4. 4.
    Cole, A., Albicki, A.: Algorithm for nonintrusive identification of residential appliances. In: Proceedings of the 1998 IEEE ISCAS, pp. 338–341 (1998)Google Scholar
  5. 5.
    Baranski, M., Voss, J.: Non-Intrusive Appliance Load Monitoring Based on an Optical Sensor. In: EEE Power Tech Conference, Bologna (2003)Google Scholar
  6. 6.
    Baranski, M., Voss, J.: Genetic Algorithm for Pattern Detection in NIALM Systems. In: IEEE International Conference on Systems, Man and Cybernetics, pp. 3462–3468 (2004)Google Scholar
  7. 7.
    Baranski, M., Voss, J.: Detecting Patterns of Appliances from Total Load Data Using a Dynamic Programming Approach. In: Fourth IEEE International Conference on Data Mining, ICDM 2004 (2004)Google Scholar
  8. 8.
    Leeb, S.B., Kirtley, J.L., Levan, M.S., Sweeney, J.P.: Development and Validation of a Transient Event Detector. AMP J. of Technology, 69–74 (1993)Google Scholar
  9. 9.
    Leeb, S.B., Shaw, S.R., Kirtley, J.L.: Transient Event Detection in Spectral Envelope Estimates. Power, 1200–1210 (1995)Google Scholar
  10. 10.
    Cox, R., Leeb, S.B., Shaw, S.R., Norford, L.K.: Transient Event Detection for Nonintrusive Load Monitoring and Demand Side Management Using Voltage Distortion. Computer Engineering, 1751–1757 (2006)Google Scholar
  11. 11.
    Chang, H.-H., Yang, H.-T., Lin, C.-L.: Load Identification in Neural Networks for a Non-intrusive Monitoring of Industrial Electrical Loads. In: Shen, W., Yong, J., Yang, Y., Barthès, J.-P.A., Luo, J. (eds.) CSCWD 2007. LNCS, vol. 5236, pp. 664–674. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  12. 12.
    Stockwell, R.G., Mansinha, L., Lowe, R.P.: Localization of the complex spectrum: the S transform. IEEE Trans. Signal Processing, 998–1001 (1996)Google Scholar
  13. 13.
    Martins, J.F., Lopes, R., Lima, C., Romero-Cadaval, E., Vinnikov, D.: A Novel Nonintrusive Load Monitoring System Based on the S-Transform. In: 13th International Conference on Optimization of Electrical and Electronic Equipment (OPTIM 2012), Brasov, Romania, May 24-26 (2012)Google Scholar
  14. 14.
    Pérez-Romero, M., Gallardo-Lozano, J., Romero-Cadaval, E., Lozano-Tello, A.: Local Energy Management Unit for Residential Applications. Electronics and Electrical Engineering 19(7), 61–64 (2013)CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2014

Authors and Affiliations

  • Máximo Pérez-Romero
    • 1
    • 2
  • Enrique Romero-Cadaval
    • 1
  • Adolfo Lozano-Tello
    • 2
  • João Martins
    • 3
  • Rui Lopes
    • 3
  1. 1.Power Electrical & Electronics Systems R+D+i GroupUniversity of Extremadura, Escuela de Ingenierías IndustrialesBadajozSpain
  2. 2.Quercus Software Engineering GroupUniversity of Extremadura, Escuela PolitécnicaCáceresSpain
  3. 3.Universidade Nova de Lisboa-FCT-DEE and UNINOVA-CTSMonte de CaparicaPortugal

Personalised recommendations