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Non-technical losses (NTL) such as electricity theft cause significant harm to our economies, as in some countries they may range up to 40% of the total electricity distributed. Detecting NTLs requires costly on-site inspections. Accurate…

Machine Learning · Computer Science 2017-07-26 Patrick O. Glauner , Andre Boechat , Lautaro Dolberg , Radu State , Franck Bettinger , Yves Rangoni , Diogo Duarte

In order to keep track of the operational state of power grid, the world's largest sensor systems, smart grid, was built by deploying hundreds of millions of smart meters. Such system makes it possible to discover and make quick response to…

Machine Learning · Computer Science 2019-07-10 Jiangteng Li , Fei Wang

Non-technical losses (NTL) occur during the distribution of electricity in power grids and include, but are not limited to, electricity theft and faulty meters. In emerging countries, they may range up to 40% of the total electricity…

Machine Learning · Computer Science 2017-07-26 Patrick Glauner , Angelo Migliosi , Jorge Meira , Petko Valtchev , Radu State , Franck Bettinger

Electricity theft is a major problem around the world in both developed and developing countries and may range up to 40% of the total electricity distributed. More generally, electricity theft belongs to non-technical losses (NTL), which…

Machine Learning · Computer Science 2017-07-26 Patrick Glauner , Jorge Meira , Lautaro Dolberg , Radu State , Franck Bettinger , Yves Rangoni , Diogo Duarte

Detection of non-technical losses (NTL) which include electricity theft, faulty meters or billing errors has attracted increasing attention from researchers in electrical engineering and computer science. NTLs cause significant harm to the…

Artificial Intelligence · Computer Science 2017-07-26 Patrick Glauner , Jorge Augusto Meira , Petko Valtchev , Radu State , Franck Bettinger

Non-technical losses (NTL) in electric power grids arise through electricity theft, broken electric meters or billing errors. They can harm the power supplier as well as the whole economy of a country through losses of up to 40% of the…

Cryptography and Security · Computer Science 2018-04-17 Niklas Dahringer

Electricity theft, or non-technical loss (NTL), presents a persistent threat to global power systems, driving significant financial deficits and compromising grid stability. Conventional detection methodologies, predominantly reactive and…

Machine Learning · Computer Science 2026-03-24 Adewale U. Oguntola , Olowookere A. AbdulQoyum , Adebukola M. Madehin , Adekemi A. Adetoro

Implementing systems based on Machine Learning to detect fraud and other Non-Technical Losses (NTL) is challenging: the data available is biased, and the algorithms currently used are black-boxes that cannot be either easily trusted or…

Machine Learning · Computer Science 2021-08-18 Bernat Coma-Puig , Josep Carmona

Extreme weather events are increasingly common due to climate change, posing significant risks. To mitigate further damage, a shift towards renewable energy is imperative. Unfortunately, underrepresented communities that are most affected…

Computer Vision and Pattern Recognition · Computer Science 2024-10-02 Alejandro Aparcedo , Christian Lopez , Abhinav Kotta , Mengjie Li

With the growing demand for energy and increased environmental awareness, Non-Intrusive Load Monitoring (NILM) has become an essential tool in smart grid and energy management. By analyzing total power load data, NILM infers the energy…

Machine Learning · Computer Science 2024-10-22 DengYu Shi

Electricity theft and non-technical losses (NTLs) remain critical challenges in modern smart grids, causing significant economic losses and compromising grid reliability. This study introduces the SmartGuard Energy Intelligence System…

Artificial intelligence-based techniques applied to the electricity consumption data generated from the smart grid prove to be an effective solution in reducing Non Technical Loses (NTLs), thereby ensures safety, reliability, and security…

Machine Learning · Computer Science 2021-10-12 Yogesh Kulkarni , Sayf Hussain Z , Krithi Ramamritham , Nivethitha Somu

Accurate load forecasting is critical for electricity market operations and other real-time decision-making tasks in power systems. This paper considers the short-term load forecasting (STLF) problem for residential customers within a…

Machine Learning · Computer Science 2021-11-24 Yuqi Zhou , Arun Sukumaran Nair , David Ganger , Abhinandan Tripathi , Chaitanya Baone , Hao Zhu

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) 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

Energy disaggregation (a.k.a nonintrusive load monitoring, NILM), a single-channel blind source separation problem, aims to decompose the mains which records the whole house electricity consumption into appliance-wise readings. This problem…

Applications · Statistics 2018-01-19 Chaoyun Zhang , Mingjun Zhong , Zongzuo Wang , Nigel Goddard , Charles Sutton

Traditionally power distribution networks are either not observable or only partially observable. This complicates development and implementation of new smart grid technologies, such as those related to demand response, outage detection and…

Optimization and Control · Mathematics 2015-03-02 Deepjyoti Deka , Scott Backhaus , Michael Chertkov

Ensuring the safety and reliability of power grids is critical as global energy demands continue to rise. Traditional inspection methods, such as manual observations or helicopter surveys, are resource-intensive and lack scalability. This…

Computer Vision and Pattern Recognition · Computer Science 2025-02-19 Diogo Lavado , Ricardo Santos , Andre Coelho , Joao Santos , Alessandra Micheletti , Claudia Soares

Electric grids in low- and middle-income countries (LMICs) across the world face an acute challenge. To support global decarbonisation efforts and raise millions from energy poverty, these grids must shoulder substantial load growth while…

Systems and Control · Electrical Eng. & Systems 2025-06-27 Mohini Bariya , Genevieve Flaspohler

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
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