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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…

Machine Learning · Computer Science 2021-04-19 Sobhan Naderian

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…

Machine Learning · Computer Science 2023-03-08 Jinsong Wang , Kenneth A. Loparo

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…

Machine Learning · Computer Science 2018-11-19 Changho Shin , Sunghwan Joo , Jaeryun Yim , Hyoseop Lee , Taesup Moon , Wonjong Rhee

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…

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…

Signal Processing · Electrical Eng. & Systems 2021-11-10 Ronak Aghera , Sahil Chilana , Vishal Garg , Raghunath Reddy

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.…

Signal Processing · Electrical Eng. & Systems 2023-06-09 Mohammad Irani Azad , Roozbeh Rajabi , Abouzar Estebsari

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 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

The growing global energy demand and the urgent need for sustainability call for innovative ways to boost energy efficiency. While advanced energy-saving systems exist, they often fall short without user engagement. Providing feedback on…

Machine Learning · Computer Science 2025-05-13 Sotirios Athanasoulias

Non-intrusive load monitoring (NILM) has been extensively researched over the last decade. The objective of NILM is to identify the power consumption of individual appliances and to detect when particular devices are on or off from…

Machine Learning · Computer Science 2021-09-16 Jordan Holweger , Marina Dorokhova , Lionel Bloch , Christophe Ballif , Nicolas Wyrsch

Energy disaggregation, also known as non-intrusive load monitoring (NILM), challenges the problem of separating the whole-home electricity usage into appliance-specific individual consumptions, which is a typical application of data…

Signal Processing · Electrical Eng. & Systems 2021-08-05 Zhekai Du , Jingjing Li , Lei Zhu , Ke Lu , Heng Tao Shen

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.…

Other Computer Science · Computer Science 2018-07-03 Dominik Egarter , Wilfried Elmenreich

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…

Machine Learning · Computer Science 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…

Signal Processing · Electrical Eng. & Systems 2021-04-16 Akriti Verma , Adnan Anwar , M. A. Parvez Mahmud , Mohiuddin Ahmed , Abbas Kouzani

With the increased demand on economy and efficiency of measurement technology, Non-Intrusive Load Monitoring (NILM) has received more and more attention as a cost-effective way to monitor electricity and provide feedback to users. Deep…

Machine Learning · Computer Science 2020-09-28 Gan Zhou , Zhi Li , Meng Fu , Yanjun Feng , Xingyao Wang , Chengwei Huang

Energy disaggregation in a non-intrusive way estimates appliance level electricity consumption from a single meter that measures the whole house electricity demand. Recently, with the ongoing increment of energy data, there are many…

Machine Learning · Computer Science 2019-03-20 Peng Xiao , Samuel Cheng

Non-intrusive load monitoring (NILM) is a well-known single-channel blind source separation problem that aims to decompose the household energy consumption into itemised energy usage of individual appliances. In this way, considerable…

Machine Learning · Computer Science 2021-06-02 Yu Zhang , Guoming Tang , Qianyi Huang , Yi Wang , Hong Xu

Non-intrusive Load Monitoring (NILM) is an established technique for effective and cost-efficient electricity consumption management. The method is used to estimate appliance-level power consumption from aggregated power measurements. This…

Systems and Control · Electrical Eng. & Systems 2023-11-16 Amanie Azzam , Saba Sanami , Amir G. Aghdam

We consider the problem of learning the energy disaggregation signals for residential load data. Such task is referred as non-intrusive load monitoring (NILM), and in order to find individual devices' power consumption profiles based on…

Machine Learning · Computer Science 2022-11-29 Ruohong Liu , Yize Chen

Non-intrusive load monitoring (NILM), aims to infer the power profiles of appliances from the aggregated power signal via purely analytical methods. Existing NILM methods are susceptible to various issues such as the noise and transient…

Systems and Control · Electrical Eng. & Systems 2020-09-08 Elnaz Azizi , Mohammad TH Beheshti , Sadegh Bolouki
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