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A feasibility study of automated plug-load identification from high-frequency measurements

Abstract: 

Plug-meters benefit many grid and building-level energy management applications like automated load control and load scheduling. However, installing and maintaining large and/orlong term deployments of such meters requires assignment and updating of the identity (labels) of electrical loads connected to them. Although the literature on electricity disaggregation and appliance identification is extensive, there is no consensus on the generalizability of the proposed solutions, especially with respect to the features that are extracted from voltage and current measurements. In this paper, we begin to address this problem by comparing the discriminative power of commonly used features. Specifically, we carry out tests on PLAID, a publicly available high-frequency dataset of hundreds of residential appliances. By examining how the classification accuracy changes with sampling
frequency, we also explore the computational complexity of these techniques to understand the feasibility and design of a hardware setup that can perform these calculations in near real-time.

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Paper Details

Authors:
Emre Can Kara, Suman Giri, Mario Berges
Submitted On:
23 February 2016 - 1:44pm
Short Link:
Type:
Presentation Slides
Event:
Presenter's Name:
Jingkun Gao
Document Year:
2015
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A feasibility study of automated plug-load identification from high-frequency measurements.pdf

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[1] Emre Can Kara, Suman Giri, Mario Berges, "A feasibility study of automated plug-load identification from high-frequency measurements", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/334. Accessed: May. 26, 2019.
@article{334-15,
url = {http://sigport.org/334},
author = {Emre Can Kara; Suman Giri; Mario Berges },
publisher = {IEEE SigPort},
title = {A feasibility study of automated plug-load identification from high-frequency measurements},
year = {2015} }
TY - EJOUR
T1 - A feasibility study of automated plug-load identification from high-frequency measurements
AU - Emre Can Kara; Suman Giri; Mario Berges
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/334
ER -
Emre Can Kara, Suman Giri, Mario Berges. (2015). A feasibility study of automated plug-load identification from high-frequency measurements. IEEE SigPort. http://sigport.org/334
Emre Can Kara, Suman Giri, Mario Berges, 2015. A feasibility study of automated plug-load identification from high-frequency measurements. Available at: http://sigport.org/334.
Emre Can Kara, Suman Giri, Mario Berges. (2015). "A feasibility study of automated plug-load identification from high-frequency measurements." Web.
1. Emre Can Kara, Suman Giri, Mario Berges. A feasibility study of automated plug-load identification from high-frequency measurements [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/334