TY - JOUR
T1 - Implementation of a robust real-time non-intrusive load monitoring solution
AU - Welikala, Shirantha
AU - Thelasingha, Neelanga
AU - Akram, Muhammed
AU - Ekanayake, Parakrama B.
AU - Godaliyadda, Roshan I.
AU - Ekanayake, Janaka B.
N1 - Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2019/3/15
Y1 - 2019/3/15
N2 - 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.
AB - 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.
KW - Demand side management
KW - Non-intrusive load monitoring
KW - Real-time load monitoring
KW - Smart grid
KW - Subspace techniques
KW - Supply voltage variation
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U2 - 10.1016/j.apenergy.2019.01.167
DO - 10.1016/j.apenergy.2019.01.167
M3 - Article
AN - SCOPUS:85060750039
SN - 0306-2619
VL - 238
SP - 1519
EP - 1529
JO - Applied Energy
JF - Applied Energy
ER -