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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…

动力系统 · 数学 2013-04-04 Roy Dong , Lillian Ratliff , Henrik Ohlsson , S. Shankar Sastry

Energy disaggregation or nonintrusive load monitoring (NILM), is a single-input blind source discrimination problem, aims to interpret the mains user electricity consumption into appliance level measurement. This article presents a new…

机器学习 · 计算机科学 2021-04-19 Sobhan Naderian

Non-intrusive load monitoring (NILM) is the task of disaggregating the total power consumption into its individual sub-components. Over the years, signal processing and machine learning algorithms have been combined to achieve this. A lot…

The importance of Non-Intrusive Load Monitoring (NILM) has been increasingly recognized, given that NILM can enhance energy awareness and provide valuable insights for energy program design. Many existing NILM methods often rely on…

信号处理 · 电气工程与系统科学 2024-09-04 Xiangrui Li

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…

Non-intrusive load monitoring (NILM) focuses on disaggregating total household power consumption into appliance-specific usage. Many advanced NILM methods are based on neural networks that typically require substantial amounts of labeled…

机器学习 · 计算机科学 2024-11-26 Dhruv Patel , Ankita Kumari Jain , Haikoo Khandor , Xhitij Choudhary , Nipun Batra

The housing structures have changed with urbanization and the growth due to the construction of high-rise buildings all around the world requires end-use appliance energy conservation and management in real-time. This shift also came along…

信号处理 · 电气工程与系统科学 2021-04-16 Akriti Verma , Adnan Anwar , M. A. Parvez Mahmud , Mohiuddin Ahmed , Abbas Kouzani

Non-intrusive load monitoring (NILM) is a technique that uses a single sensor to measure the total power consumption of a building. Using an energy disaggregation method, the consumption of individual appliances can be estimated from the…

机器学习 · 计算机科学 2021-07-21 Antoine Langevin , Marc-André Carbonneau , Mohamed Cheriet , Ghyslain Gagnon

Individual device loads and energy consumption feedback is one of the important approaches for pursuing users to save energy in residences. This can help in identifying faulty devices and wasted energy by devices when left On unused. The…

信号处理 · 电气工程与系统科学 2021-11-10 Ronak Aghera , Sahil Chilana , Vishal Garg , Raghunath Reddy

Energy disaggregation, known in the literature as Non-Intrusive Load Monitoring (NILM), is the task of inferring the power demand of the individual appliances given the aggregate power demand recorded by a single smart meter which monitors…

机器学习 · 计算机科学 2021-02-09 Veronica Piccialli , Antonio M. Sudoso

Energy disaggregation, known in the literature as Non-Intrusive Load Monitoring (NILM), is the task of inferring the energy consumption of each appliance given the aggregate signal recorded by a single smart meter. In this paper, we propose…

最优化与控制 · 数学 2022-04-13 Marco Balletti , Veronica Piccialli , Antonio M. Sudoso

With the help of smart metering valuable information of the appliance usage can be retrieved. In detail, non-intrusive load monitoring (NILM), also called load disaggregation, tries to identify appliances in the power draw of an household.…

其他计算机科学 · 计算机科学 2018-07-03 Dominik Egarter , Wilfried Elmenreich

Demand-side management now encompasses more residential loads. To efficiently apply demand response strategies, it's essential to periodically observe the contribution of various domestic appliances to total energy consumption.…

信号处理 · 电气工程与系统科学 2023-06-09 Mohammad Irani Azad , Roozbeh Rajabi , Abouzar Estebsari

Non-intrusive load monitoring (NILM) aims at decomposing the total reading of the household power consumption into appliance-wise ones, which is beneficial for consumer behavior analysis as well as energy conservation. NILM based on deep…

信号处理 · 电气工程与系统科学 2021-05-25 Haijin Wang , Caomingzhe Si , Junhua Zhao

Non-intrusive load monitoring (NILM), also known as energy disaggregation, is a blind source separation problem where a household's aggregate electricity consumption is broken down into electricity usages of individual appliances. In this…

机器学习 · 计算机科学 2018-11-19 Changho Shin , Sunghwan Joo , Jaeryun Yim , Hyoseop Lee , Taesup Moon , Wonjong Rhee

Non-Intrusive Load Monitoring (NILM) is a technology offering methods to identify appliances in homes based on their consumption characteristics and the total household demand. Recently, many different novel NILM approaches were introduced,…

其他计算机科学 · 计算机科学 2015-01-14 Dominik Egarter , Manfred Pöchacker , Wilfried Elmenreich

Non intrusive load monitoring (NILM), or energy disaggregation, is the process of separating the total electricity consumption of a building as measured at single point into the building's constituent loads. Previous research in the field…

系统与控制 · 计算机科学 2014-08-29 Nipun Batra , Oliver Parson , Mario Berges , Amarjeet Singh , Alex Rogers

Non-Intrusive Load Monitoring (NILM) is an energy efficiency technique to track electricity consumption of an individual appliance in a household by one aggregated single, such as building level meter readings. The goal of NILM is to…

机器学习 · 计算机科学 2023-03-08 Jinsong Wang , Kenneth A. Loparo

Non-Intrusive Load Monitoring (NILM) comprises of a set of techniques that provide insights into the energy consumption of households and industrial facilities. Latest contributions show significant improvements in terms of accuracy and…

信号处理 · 电气工程与系统科学 2020-01-23 Christoph Klemenjak , Stephen Makonin , Wilfried Elmenreich

Non-intrusive load monitoring (NILM), which usually utilizes machine learning methods and is effective in disaggregating smart meter readings from the household-level into appliance-level consumptions, can help to analyze electricity…

机器学习 · 计算机科学 2021-08-10 Shuang Dai , Fanlin Meng , Qian Wang , Xizhong Chen
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