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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

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

In recent times, non-intrusive load monitoring (NILM) has emerged as an important tool for distribution-level energy management systems owing to its potential for energy conservation and management. However, load monitoring in smart…

Systems and Control · Electrical Eng. & Systems 2022-06-01 Himanshu Grover , Lokesh Panwar , Ashu Verma , B. K. Panigrahi , T. S. Bhatti

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…

Machine Learning · Computer Science 2021-02-09 Veronica Piccialli , Antonio M. Sudoso

Non-Intrusive Load Monitoring (NILM) is a practical method to provide appliance-level electricity consumption information. Event detection, as an important part of event-based NILM methods, has a direct impact on the accuracy of the…

Signal Processing · Electrical Eng. & Systems 2019-03-25 Mengqi Lu , Zuyi Li

Residential buildings with the ability to monitor and control their net-load (sum of load and generation) can provide valuable flexibility to power grid operators. We present a novel multiclass nonintrusive load monitoring (NILM) approach…

Machine Learning · Computer Science 2022-08-24 Govind Saraswat , Blake Lundstrom , Murti V Salapaka

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

Non-intrusive load monitoring (NILM) as the process of extracting the usage pattern of appliances from the aggregated power signal is among successful approaches aiding residential energy management. In recent years, high volume datasets on…

Systems and Control · Electrical Eng. & Systems 2021-01-19 Mohammad-Mehdi Keramati , Elnaz Azizi , Hamidreza Momeni , Sadegh Bolouki

Non-Intrusive Load Monitoring (NILM) identifies the operating status and energy consumption of each electrical device in the circuit by analyzing the electrical signals at the bus, which is of great significance for smart power management.…

Machine Learning · Computer Science 2025-06-10 Olimjon Toirov , Wei Yu

Non-intrusive load monitoring (NILM) is the process of obtaining appliance-level data from a single metering point, measuring total electricity consumption of a household or a business. Appliance-level data can be directly used for demand…

Machine Learning · Computer Science 2024-04-01 Anže Pirnat , Blaž Bertalanič , Gregor Cerar , Mihael Mohorčič , Carolina Fortuna

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) aims to decompose aggregated electrical usage signal into appliance-specific power consumption and it amounts to a classical example of blind source separation tasks. Leveraging recent progress on deep…

Machine Learning · Computer Science 2023-02-14 Jialing He , Jiamou Liu , Zijian Zhang , Yang Chen , Yiwei Liu , Bakh Khoussainov , Liehuang Zhu

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) 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

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

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…

Signal Processing · Electrical Eng. & Systems 2024-09-04 Xiangrui Li

Non-Intrusive Load Monitoring (NILM) is the method of detecting an individual device's energy signal from an aggregated energy consumption signature [1]. As existing energy meters provide very little to no information regarding the energy…

Machine Learning · Computer Science 2020-12-23 Mohammad Mahmudur Rahman Khan , Md. Abu Bakr Siddique , Shadman Sakib

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) 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

Non-intrusive load monitoring (NILM) is a key cost-effective technology for monitoring power consumption and contributing to several challenges encountered when transiting to an efficient, sustainable, and competitive energy efficiency…

Computers and Society · Computer Science 2021-02-10 Yassine Himeur , Abdullah Alsalemi , Faycal Bensaali , Abbes Amira
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