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Residential smart meters have been widely installed in urban houses nationwide to provide efficient and responsive monitoring and billing for consumers. Studies have shown that providing customers with device-level usage information can…

Signal Processing · Electrical Eng. & Systems 2020-07-14 Mengheng Xue , Samantha Kappagoda , David K. A. Mordecai

Electricity consumed by residential consumers counts for a significant part of global electricity consumption and utility companies can collect high-resolution load data thanks to the widely deployed advanced metering infrastructure. There…

Human-Computer Interaction · Computer Science 2021-03-11 Hao Wang , Gonzague Henri , Chin-Woo Tan , Ram Rajagopal

Smart energy management based on the Internet of Things (IoT) aims to achieve optimal energy utilization through real-time energy monitoring and analyses of power consumption patterns in IoT networks (e.g., residential homes and offices)…

Systems and Control · Electrical Eng. & Systems 2023-12-01 Guang-Li Huang , Adnan Anwar , Seng W. Loke , Arkady Zaslavsky , Jinho Choi

Energy disaggregation, a.k.a. Non-Intrusive Load Monitoring, aims to separate the energy consumption of individual appliances from the readings of a mains power meter measuring the total energy consumption of, e.g. a whole house. Energy…

Machine Learning · Computer Science 2019-08-06 Jie Jiang , Qiuqiang Kong , Mark Plumbley , Nigel Gilbert

Energy disaggregation is the process of estimating the energy consumed by individual electrical appliances given only a time series of the whole-home power demand. Energy disaggregation researchers require datasets of the power demand from…

Databases · Computer Science 2015-09-23 Jack Kelly , William Knottenbelt

Most electricity systems worldwide are deploying advanced metering infrastructures to collect relevant operational data. In particular, smart meters allow tracking electricity load consumption at a very disaggregated level and at high…

Machine Learning · Statistics 2020-03-09 Andrés M. Alonso , F. Javier Nogales , Carlos Ruiz

Energy disaggregation is the task of segregating the aggregate energy of the entire building (as logged by the smartmeter) into the energy consumed by individual appliances. This is a single channel (the only channel being the smart-meter)…

Signal Processing · Electrical Eng. & Systems 2019-12-30 Shikha Singh , Angshul Majumdar

In the residential sector, electric water heaters are appliances with a relatively high power consumption and a significant thermal inertia, which is particularly suitable for Demand Response schemes. The success of efficient DR schemes via…

Systems and Control · Electrical Eng. & Systems 2021-04-08 Thierry Zufferey , Gustavo Valverde , Gabriela Hug

One of the most far-reaching use cases of the internet of things is in smart grid and smart home operation. The smart home concept allows residents to control, monitor, and manage their energy consumption with minimum loss and…

Systems and Control · Electrical Eng. & Systems 2025-02-11 S. Saba Rafiei , Mahdi S. Naderi , Mehrdad Abedi

Energy disaggregation estimates appliance-by-appliance electricity consumption from a single meter that measures the whole home's electricity demand. Recently, deep neural networks have driven remarkable improvements in classification…

Neural and Evolutionary Computing · Computer Science 2015-09-29 Jack Kelly , William Knottenbelt

Energy disaggregation, also known as non-intrusive load monitoring (NILM), is the task of separating aggregate energy data for a whole building into the energy data for individual appliances. Studies have shown that simply providing…

Dynamical Systems · Mathematics 2013-04-04 Roy Dong , Lillian Ratliff , Henrik Ohlsson , S. Shankar Sastry

Energy disaggregation is the task of segregating the aggregate energy of the entire building (as logged by the smartmeter) into the energy consumed by individual appliances. This is a single channel (the only channel being the smart-meter)…

Signal Processing · Electrical Eng. & Systems 2019-12-30 Shikha Singh , Angshul Majumdar

Non-intrusive load monitoring or energy disaggregation involves estimating the power consumption of individual appliances from measurements of the total power consumption of a home. Deep neural networks have been shown to be effective for…

Machine Learning · Computer Science 2018-12-11 Cillian Brewitt , Nigel Goddard

In this paper, we investigate whether "big-data" is more valuable than "precise" data for the problem of energy disaggregation: the process of breaking down aggregate energy usage on a per-appliance basis. Existing techniques for…

Machine Learning · Computer Science 2015-11-11 Nipun Batra , Amarjeet Singh , Kamin Whitehouse

Investigations have been performed into using clustering methods in data mining time-series data from smart meters. The problem is to identify patterns and trends in energy usage profiles of commercial and industrial customers over 24-hour…

Machine Learning · Statistics 2016-03-25 Alexander Lavin , Diego Klabjan

The rapid urbanization of developing countries coupled with explosion in construction of high rising buildings and the high power usage in them calls for conservation and efficient energy program. Such a program require monitoring of…

Other Computer Science · Computer Science 2017-03-13 Anthony Faustine , Nerey Henry Mvungi , Shubi Kaijage , Kisangiri Michael

Energy disaggregation determines the energy consumption of individual appliances from the total demand signal, which is recorded using a single monitoring device. There are varied approaches to this problem, which are applied to different…

Signal Processing · Electrical Eng. & Systems 2018-03-02 Laura Hattam , Danica Vukadinovic Greetham

Non-intrusive load monitoring (NILM) or energy disaggregation aims to extract the load profiles of individual consumer electronic appliances, given an aggregate load profile of the mains of a smart home. This work proposes a novel…

Energy is a limited resource which has to be managed wisely, taking into account both supply-demand matching and capacity constraints in the distribution grid. One aspect of the smart energy management at the building level is given by the…

Machine Learning · Statistics 2016-05-09 Elena Mocanu , Phuong H. Nguyen , Madeleine Gibescu

The smart meter data analysis contributes to better planning and operations for the power system. This study aims to identify the drivers of residential energy consumption patterns from the socioeconomic perspective based on the consumption…

Machine Learning · Computer Science 2021-11-03 Wenjun Tang , Hao Wang , Xian-Long Lee , Hong-Tzer Yang
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