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Load Signature Formulation for Non-Intrusive Load Monitoring Based on Current Measurements

Author

Listed:
  • Aggelos S. Bouhouras

    (Electrical Power Laboratory, Department of Electrical Engineering, Western Macedonia University of Applied Sciences, 50100 Kozani, Greece)

  • Paschalis A. Gkaidatzis

    (Power Systems Laboratory, Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

  • Konstantinos C. Chatzisavvas

    (Electrical Power Laboratory, Department of Electrical Engineering, Western Macedonia University of Applied Sciences, 50100 Kozani, Greece
    mSensis S.A., VEPE Technopolis, Bld. C2, P.O. Box 60756, 57001 Thessaloniki, Greece)

  • Evangelos Panagiotou

    (Electrical Power Laboratory, Department of Electrical Engineering, Western Macedonia University of Applied Sciences, 50100 Kozani, Greece)

  • Nikolaos Poulakis

    (Electrical Power Laboratory, Department of Electrical Engineering, Western Macedonia University of Applied Sciences, 50100 Kozani, Greece)

  • Georgios C. Christoforidis

    (Electrical Power Laboratory, Department of Electrical Engineering, Western Macedonia University of Applied Sciences, 50100 Kozani, Greece)

Abstract

In this paper we present a new methodology for the formulation of efficient load signatures towards the implementation of a near-real time Non-Intrusive Load Monitoring (NILM) approach. The purpose of this work relies on defining representative current values regarding the 1st, 3rd and 5th harmonic orders to be utilized in the load signatures formulation. A measurement setup has been developed and steady-state measurements have been performed in a Low Voltage residence. A data processing methodology is proposed aiming to depict representative current values for each harmonic order in order to keep the load signature short and simple. In addition, a simple disaggregation scheme is proposed under linear equations for the disaggregation mode in order to examine the near-real time application of the methodology. The analysis indicates that the developed load signatures could be efficient for a per second application rate of the NILM algorithm. The results show that the higher harmonic currents facilitate the identification performance. Finally, the analysis concludes that for combinations that include appliances with intense harmonic content, the phase angle of the higher for harmonic currents should also be considered to the load signatures formulation.

Suggested Citation

  • Aggelos S. Bouhouras & Paschalis A. Gkaidatzis & Konstantinos C. Chatzisavvas & Evangelos Panagiotou & Nikolaos Poulakis & Georgios C. Christoforidis, 2017. "Load Signature Formulation for Non-Intrusive Load Monitoring Based on Current Measurements," Energies, MDPI, vol. 10(4), pages 1-21, April.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:4:p:538-:d:95934
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    References listed on IDEAS

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    1. Ying-Yi Hong & Jing-Han Chou, 2012. "Nonintrusive Energy Monitoring for Microgrids Using Hybrid Self-Organizing Feature-Mapping Networks," Energies, MDPI, vol. 5(7), pages 1-16, July.
    2. Hsueh-Hsien Chang, 2012. "Non-Intrusive Demand Monitoring and Load Identification for Energy Management Systems Based on Transient Feature Analyses," Energies, MDPI, vol. 5(11), pages 1-21, November.
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    Citations

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    Cited by:

    1. Younghoon Kwak & Jihyun Hwang & Taewon Lee, 2018. "Load Disaggregation via Pattern Recognition: A Feasibility Study of a Novel Method in Residential Building," Energies, MDPI, vol. 11(4), pages 1-22, April.
    2. Wesley Angelino de Souza & Fernando Deluno Garcia & Fernando Pinhabel Marafão & Luiz Carlos Pereira da Silva & Marcelo Godoy Simões, 2019. "Load Disaggregation Using Microscopic Power Features and Pattern Recognition," Energies, MDPI, vol. 12(14), pages 1-18, July.
    3. Hari Prasad Devarapalli & V. S. S. Siva Sarma Dhanikonda & Sitarama Brahmam Gunturi, 2020. "Non-Intrusive Identification of Load Patterns in Smart Homes Using Percentage Total Harmonic Distortion," Energies, MDPI, vol. 13(18), pages 1-15, September.
    4. Anwar Ul Haq & Hans-Arno Jacobsen, 2018. "Prospects of Appliance-Level Load Monitoring in Off-the-Shelf Energy Monitors: A Technical Review," Energies, MDPI, vol. 11(1), pages 1-22, January.
    5. Pascal A. Schirmer & Iosif Mporas, 2019. "Statistical and Electrical Features Evaluation for Electrical Appliances Energy Disaggregation," Sustainability, MDPI, vol. 11(11), pages 1-14, June.
    6. Antonio Ruano & Alvaro Hernandez & Jesus Ureña & Maria Ruano & Juan Garcia, 2019. "NILM Techniques for Intelligent Home Energy Management and Ambient Assisted Living: A Review," Energies, MDPI, vol. 12(11), pages 1-29, June.
    7. Yuval Beck & Ram Machlev, 2019. "Harmonic Loads Classification by Means of Currents’ Physical Components," Energies, MDPI, vol. 12(21), pages 1-18, October.

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