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Occupancy-aided energy disaggregation
Computer Networks, 2017Energy disaggregation helps to identify major energy guzzlers in the house without introducing extra metering cost. It motivates users to take proper actions for energy saving and facilitates demand response programs. To reduce the computational complexity of pure energy disaggregation, we propose an occupancy-aided energy disaggregation (OAED ...
Guoming Tang +4 more
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Energy Disaggregation Using Fractional Calculus
ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020Non-Intrusive Load Monitoring aims to extract the energy consumption of individual electrical appliances through disaggregation of the total power load measured by one smart-meter. In this article we introduce the use of fractional calculus in the Non-Intrusive Load Monitoring task.
Pascal A. Schirmer, Iosif Mporas
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Energy disaggregation meets heating control
Proceedings of the 29th Annual ACM Symposium on Applied Computing, 2014Heating control is of particular importance, since heating accounts for the biggest amount of total residential energy consumption. Smart heating strategies allow to reduce such energy consumption by automatically turning off the heating when the occupants are sleeping or away from home.
Stephan Spiegel, Sahin Albayrak
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Disaggregation of sandstones by ultrasonic energy
Journal of Sedimentary Research, 1970A rapid method of disaggregating sandstones was investigated, with emphasis on reducing specimens to individual grains without destroying surficial or volumetric parameters. Specific quantities of samples were used to test three ultrasonic generators with focused horns utilizing varying degrees of acoustical intensity and frequencies for preset periods
W. K. Overbey, B. R. Henniger
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Energy Disaggregation via Data Mining
2019Electrical energy consumption of a residence is usually monitored by a meter installed at its entrance and it is composed by the sum of consumptions of installed devices. Energy disaggregation estimates the consumption of each device at each instant of time. This paper presents two main contributions.
Pierre Dantas +2 more
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Energy disaggregation using ensemble of classifiers
IEEE 2013 Tencon - Spring, 2013We study an approach towards energy disaggregation using ensemble of classifiers, a supervised machine learning method. Specifically we identify different appliance loads from the aggregated power usage data. Experimental results on a public data sets show the accuracy of ensemble of classifiers using diverse features in identifying appliance loads.
Md. Sumon Shahriar, Ashfaqur Rahman
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Disaggregate Household Energy Requirements
2007Previous chapters of the book have focused on how to combine aggregate input-output data and energy flows to calculate energy intensities of broad sectors and use these calculated intensities in conjunction with micro-level disaggregate household survey data to analyse variations in direct and indirect energy use patters across different types of ...
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Deep Neural Network Based Energy Disaggregation
2018 IEEE International Conference on Smart Energy Grid Engineering (SEGE), 2018In smart electricity grids, energy disaggregation significantly contributes to better demand side management, load forecasting and energy savings via estimating appliance level energy consumption from the aggregated smart meter data. This paper proposes a deep neural network based system by combining convolutional neural networks and variational auto ...
T. Sirojan, B. T. Phung, E. Ambikairajah
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Energy disaggregation for identifying anomalous appliance
Proceedings of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments, 2017Energy disaggregation research claims that it can be used to identify anomalous appliances. Our study proposes a technique which checks how accurate is disaggregated data in identifying such appliances. The evaluation of proposed technique on four different homes shows that disaggregation enables to find anomalies in air conditioner and refrigerator ...
Haroon Rashid, Pushpendra Singh
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Unsupervised Energy Disaggregation of Home Appliances
2017Energy management is a growing concern especially with the increasing growth of smart appliances within the home. Energy disaggregation is an ongoing challenge to discover the appliance usage by examining the energy output of a household or building. Unsupervised NILM presents the additional challenge of energy disaggregation without any reliance on ...
Kondwani M. Kamoto, Qi Liu, Xiaodong Liu
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