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Implementation of a robust real-time non-intrusive load monitoring solution

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  • Welikala, Shirantha
  • Thelasingha, Neelanga
  • Akram, Muhammed
  • Ekanayake, Parakrama B.
  • Godaliyadda, Roshan I.
  • Ekanayake, Janaka B.

Abstract

This paper presents the formulation and practical implementation of a spectral decomposition based, Real-Time Non-Intrusive Load Monitoring (RT-NILM) solution. Many of the NILM techniques reported in the literature have been validated on environments with non-varying supply voltages, while relying on multiple measurements taken at high sampling rates. In contrast, the RT-NILM solution proposed in this paper has addressed the issue of supply voltage variability, which is a common practical problem prevalent in many developing countries and is anticipated to emerge globally with the increased penetration of renewable energy sources. Therefore, the proposed RT-NILM algorithm was implemented to maintain high accuracy levels even under severe supply voltage fluctuations. An iterative implementation of the Karhunen-Loève expansion was introduced to improve the spectrum decomposition resolution. Further, a fast deconvolution based technique was introduced for the disaggregation of individual power levels of active appliances in an computationally efficient manner. The proposed solution has been validated on a real voltage varying environment, at a real house, in real-time, using active power and voltage measurements taken at a low sampling rate of 1 Hz.

Suggested Citation

  • Welikala, Shirantha & Thelasingha, Neelanga & Akram, Muhammed & Ekanayake, Parakrama B. & Godaliyadda, Roshan I. & Ekanayake, Janaka B., 2019. "Implementation of a robust real-time non-intrusive load monitoring solution," Applied Energy, Elsevier, vol. 238(C), pages 1519-1529.
    • Handle: RePEc:eee:appene:v:238:y:2019:i:c:p:1519-1529
    DOI: 10.1016/j.apenergy.2019.01.167
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    References listed on IDEAS

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    1. Dinesh, Chinthaka & Welikala, Shirantha & Liyanage, Yasitha & Ekanayake, Mervyn Parakrama B. & Godaliyadda, Roshan Indika & Ekanayake, Janaka, 2017. "Non-intrusive load monitoring under residential solar power influx," Applied Energy, Elsevier, vol. 205(C), pages 1068-1080.
    2. Liu, Chao & Akintayo, Adedotun & Jiang, Zhanhong & Henze, Gregor P. & Sarkar, Soumik, 2018. "Multivariate exploration of non-intrusive load monitoring via spatiotemporal pattern network," Applied Energy, Elsevier, vol. 211(C), pages 1106-1122.
    3. Cominola, A. & Giuliani, M. & Piga, D. & Castelletti, A. & Rizzoli, A.E., 2017. "A Hybrid Signature-based Iterative Disaggregation algorithm for Non-Intrusive Load Monitoring," Applied Energy, Elsevier, vol. 185(P1), pages 331-344.
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    2. Luan, Wenpeng & Wei, Zun & Liu, Bo & Yu, Yixin, 2022. "Non-intrusive power waveform modeling and identification of air conditioning load," Applied Energy, Elsevier, vol. 324(C).
    3. Liu, Yu & Liu, Wei & Shen, Yiwen & Zhao, Xin & Gao, Shan, 2021. "Toward smart energy user: Real time non-intrusive load monitoring with simultaneous switching operations," Applied Energy, Elsevier, vol. 287(C).
    4. Wang, Y. & Mauree, D. & Sun, Q. & Lin, H. & Scartezzini, J.L. & Wennersten, R., 2020. "A review of approaches to low-carbon transition of high-rise residential buildings in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    5. Zhao, Zhida & Yu, Hao & Li, Peng & Li, Peng & Kong, Xiangyu & Wu, Jianzhong & Wang, Chengshan, 2019. "Optimal placement of PMUs and communication links for distributed state estimation in distribution networks," Applied Energy, Elsevier, vol. 256(C).
    6. Su, Hongzhi & Wang, Chengshan & Li, Peng & Liu, Zhelin & Yu, Li & Wu, Jianzhong, 2019. "Optimal placement of phasor measurement unit in distribution networks considering the changes in topology," Applied Energy, Elsevier, vol. 250(C), pages 313-322.
    7. Wang, Shuangyuan & Li, Ran & Evans, Adrian & Li, Furong, 2020. "Regional nonintrusive load monitoring for low voltage substations and distributed energy resources," Applied Energy, Elsevier, vol. 260(C).
    8. Chaminda Bandara, W.G. & Godaliyadda, G.M.R.I. & Ekanayake, M.P.B. & Ekanayake, J.B., 2020. "Coordinated photovoltaic re-phasing: A novel method to maximize renewable energy integration in low voltage networks by mitigating network unbalances," Applied Energy, Elsevier, vol. 280(C).
    9. Himeur, Yassine & Alsalemi, Abdullah & Bensaali, Faycal & Amira, Abbes, 2020. "Robust event-based non-intrusive appliance recognition using multi-scale wavelet packet tree and ensemble bagging tree," Applied Energy, Elsevier, vol. 267(C).
    10. Tekler, Zeynep Duygu & Low, Raymond & Zhou, Yuren & Yuen, Chau & Blessing, Lucienne & Spanos, Costas, 2020. "Near-real-time plug load identification using low-frequency power data in office spaces: Experiments and applications," Applied Energy, Elsevier, vol. 275(C).
    11. Su, Hongzhi & Wang, Chengshan & Li, Peng & Li, Peng & Liu, Zhelin & Wu, Jianzhong, 2019. "Novel voltage-to-power sensitivity estimation for phasor measurement unit-unobservable distribution networks based on network equivalent," Applied Energy, Elsevier, vol. 250(C), pages 302-312.
    12. Himeur, Yassine & Alsalemi, Abdullah & Bensaali, Faycal & Amira, Abbes, 2020. "Effective non-intrusive load monitoring of buildings based on a novel multi-descriptor fusion with dimensionality reduction," Applied Energy, Elsevier, vol. 279(C).

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