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Article

Non-Intrusive Identification of Load Patterns in Smart Homes Using Percentage Total Harmonic Distortion

1
Tata Consultancy Services, Hyderabad 500081, T.S., India
2
Department of Electrical Engineering, National Institute of Technology Warangal, Warangal 506004, T.S., India
*
Author to whom correspondence should be addressed.
Energies 2020, 13(18), 4628; https://doi.org/10.3390/en13184628
Received: 3 August 2020 / Revised: 29 August 2020 / Accepted: 3 September 2020 / Published: 6 September 2020
(This article belongs to the Special Issue Demand Response in Smart Grids)
Demand Response (DR) plays a vital role in a smart grid, helping consumers plan their usage patterns and optimize electricity consumption and also reduce harmonic pollution in a distribution grid without compromising on their needs. The first step of DR is the disaggregation of loads and identifying them individually. The literature suggests that this is accomplished through electric features. Present-day households are using modern power electronic-based nonlinear loads such as LED (Light Emitting Diode) lamps, electronic regulators and digital controllers to reduce the electricity consumption. Furthermore, usage of SMPS (Switched-Mode Power Supply) for computing and mobile phone chargers is increasing in every home. These nonlinear loads, while reducing electricity consumption, also introduce harmonic pollution into the distribution grid. This article presents a deterministic approach to the non-intrusive identification of load patterns using percentage Total Harmonic Distortion (THD) for DR management from a Power Quality perspective. The percentage THD of various combinations of loads is estimated by enhanced dual-spectrum line interpolated FFT (Fast Fourier Transform) with a four-term minimal side-lobe window using a LabVIEW-based hardware setup in real time. The results demonstrate that percentage THD identifies a different combination of loads effectively and advocates alternate load combinations for recommending to the consumer to reduce harmonic pollution in the distribution grid. View Full-Text
Keywords: demand response; load disaggregation; percentage total harmonic distortion and non-intrusive identification of load pattern demand response; load disaggregation; percentage total harmonic distortion and non-intrusive identification of load pattern
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MDPI and ACS Style

Devarapalli, H.P.; Dhanikonda, V.S.S.S.S.; Gunturi, S.B. Non-Intrusive Identification of Load Patterns in Smart Homes Using Percentage Total Harmonic Distortion. Energies 2020, 13, 4628. https://doi.org/10.3390/en13184628

AMA Style

Devarapalli HP, Dhanikonda VSSSS, Gunturi SB. Non-Intrusive Identification of Load Patterns in Smart Homes Using Percentage Total Harmonic Distortion. Energies. 2020; 13(18):4628. https://doi.org/10.3390/en13184628

Chicago/Turabian Style

Devarapalli, Hari P., V. S.S.S.S. Dhanikonda, and Sitarama B. Gunturi 2020. "Non-Intrusive Identification of Load Patterns in Smart Homes Using Percentage Total Harmonic Distortion" Energies 13, no. 18: 4628. https://doi.org/10.3390/en13184628

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