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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 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

With the emergence of cost effective battery storage and the decline in the solar photovoltaic (PV) levelized cost of energy (LCOE), the number of behind-the-meter solar PV systems is expected to increase steadily. The ability to estimate…

Systems and Control · Electrical Eng. & Systems 2021-05-19 Xinlei Chen , Moosa Moghimi Haji , Omid Ardakanian

Non-intrusive load monitoring (NILM) allows users and energy providers to gain insight into home appliance electricity consumption using only the building's smart meter. Most current techniques for NILM are trained using significant amounts…

Signal Processing · Electrical Eng. & Systems 2020-07-28 Alon Harell , Richard Jones , Stephen Makonin , Ivan V. Bajic

In recent years, smart meters have been widely adopted by electricity suppliers to improve the management of the smart grid system. These meters usually collect energy consumption data at a very low frequency (every 30min), enabling…

Signal Processing · Electrical Eng. & Systems 2023-05-23 Adrien Petralia , Philippe Charpentier , Paul Boniol , Themis Palpanas

An aggregate model is a single-zone equivalent of a multi-zone building, and is useful for many purposes, including model based control of large heating, ventilation and air conditioning (HVAC) equipment. This paper deals with the problem…

Systems and Control · Electrical Eng. & Systems 2020-01-27 Zhong Guo , Austin R. Coffman , Jeffrey Munk , Piljae Im , Teja Kuruganti , Prabir Barooah

Smart meters are used to measure the energy consumption of households. Specifically, within the energy consumption task smart meter have been used for load forecasting, reduction of consumer bills as well as reduction of grid distortions.…

Signal Processing · Electrical Eng. & Systems 2020-07-02 Pascal A. Schirmer , Iosif Mporas , Akbar Sheikh-Akbari

The rapid deployment of renewable generations such as photovoltaic (PV) generations brings great challenges to the resiliency of existing power systems. Because PV generations are volatile and typically invisible to the power system…

Machine Learning · Computer Science 2022-07-11 Ming Yi , Meng Wang

In this demonstration, we present an open source toolkit for evaluating non-intrusive load monitoring research; a field which aims to disaggregate a household's total electricity consumption into individual appliances. The toolkit contains:…

Other Computer Science · Computer Science 2014-11-11 Jack Kelly , Nipun Batra , Oliver Parson , Haimonti Dutta , William Knottenbelt , Alex Rogers , Amarjeet Singh , Mani Srivastava

The need for reducing our energy consumption footprint and the increasing number of electric devices in today's homes is calling for new solutions that allow users to efficiently manage their energy consumption. Real-time feedback at device…

Signal Processing · Electrical Eng. & Systems 2020-02-14 Hafsa Bousbiat , Christoph Klemenjak , Gerhard Leitner , Wilfried Elmenreich

Due to growing population and technological advances, global electricity consumption, and consequently also CO2 emissions are increasing. The residential sector makes up 25% of global electricity consumption and has great potential to…

Machine Learning · Computer Science 2025-04-15 Vid Hanžel , Blaž Bertalanič , Carolina Fortuna

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

Energy disaggregation or Non-Intrusive Load Monitoring (NILM) addresses the issue of extracting device-level energy consumption information by monitoring the aggregated signal at one single measurement point without installing meters on…

Computational Engineering, Finance, and Science · Computer Science 2018-05-16 Alireza Rahimpour , Hairong Qi , David Fugate , Teja Kuruganti

This study explores the interaction between aggregators and building occupants in activating flexibility through Demand Response (DR) programs, with a focus on reinforcing the resilience of the energy system considering the uncertainties…

Systems and Control · Electrical Eng. & Systems 2025-01-13 Costas Mylonas , Donata Boric , Leila Luttenberger Maric , Alexandros Tsitsanis , Eleftheria Petrianou , Magda Foti

Energy disaggregation refers to the decomposition of energy use time series data into its constituent loads. This paper decomposes daily use data of a household unit into fixed loads and one or more classes of shiftable loads. The latter is…

Systems and Control · Electrical Eng. & Systems 2019-08-02 Ahmad Khaled Zarabie , Sanjoy Das

In the Smart Grid environment, the advent of intelligent measuring devices facilitates monitoring appliance electricity consumption. This data can be used in applying Demand Response (DR) in residential houses through data analytics, and…

Signal Processing · Electrical Eng. & Systems 2020-08-10 Abdelkareem Jaradat , Hanan Lutfiyya , Anwar Haque

Non-intrusive load monitoring (NILM) identifies the status and power consumption of various household appliances by disaggregating the total power usage signal of an entire house. Efficient and accurate load monitoring facilitates user…

Machine Learning · Computer Science 2023-08-01 Jing Xiong , Tianqi Hong , Dongbo Zhao , Yu Zhang

In the context of the energy transition, with increasing integration of renewable sources and cross-border electricity exchanges, power grids are encountering greater uncertainty and operational risk. Maintaining grid stability under…

Machine Learning · Computer Science 2025-09-24 Milad Leyli-abadi , Antoine Marot , Jérôme Picault

A major challenge to implementing residential demand response is that of aligning the objectives of many households, each of which aims to minimize its payments and maximize its comfort level, while balancing this with the objectives of an…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-18 Sleiman Mhanna , Archie Chapman , Gregor Verbic

This paper presents a new algorithm to extract device profiles fully unsupervised from three phases reactive and active aggregate power measurements. The extracted device profiles are applied for the disaggregation of the aggregate power…

Signal Processing · Electrical Eng. & Systems 2020-07-24 Karoline Brucke , Stefan Arens , Jan-Simon Telle , Thomas Steens , Benedikt Hanke , Karsten von Maydell , Carsten Agert