English
Related papers

Related papers: Forecasting Residential Heating and Electricity De…

200 papers

The widespread deployment of Advanced Metering Infrastructure has made granular data of residential electricity consumption available on a large scale. Smart meters enable a two way communication between residential customers and utilities.…

Systems and Control · Computer Science 2016-08-15 Datong Zhou , Maximilian Balandat , Claire Tomlin

Long-term planning of a robust power system requires the understanding of changing demand patterns. Electricity demand is highly weather sensitive. Thus, the supply side variation from introducing intermittent renewable sources, juxtaposed…

Machine Learning · Computer Science 2022-09-13 Reshmi Ghosh , Michael Craig , H. Scott Matthews , Constantine Samaras , Laure Berti-Equille

Near-future electric distribution grids operation will have to rely on demand-side flexibility, both by implementation of demand response strategies and by taking advantage of the intelligent management of increasingly common small-scale…

Neural and Evolutionary Computing · Computer Science 2017-11-09 Rui Pinto , Ricardo Bessa , Manuel Matos

The residential buildings sector is one of the largest electricity consumers worldwide and contributes disproportionally to peak electricity demand in many regions. Strongly driven by occupant activities at home, household energy…

Systems and Control · Electrical Eng. & Systems 2021-11-05 Jianli Chen , Rajendra Adhikari , Eric Wilson , Joseph Robertson , Anthony Fontanini , Ben Polly , Opeoluwa Olawale

Standard (black-box) regression models may not necessarily suffice for accurate identification and prediction of thermal dynamics in buildings. This is particularly apparent when either the flow rate or the inlet temperature of the thermal…

Systems and Control · Computer Science 2016-08-11 Georgios C. Chasparis , Thomas Natschlaeger

Against the backdrop of increasingly severe global environmental changes, accurately predicting and meeting renewable energy demands has become a key challenge for sustainable business development. Traditional energy demand forecasting…

Machine Learning · Computer Science 2024-10-22 Te Li , Mengze Zhang , Yan Zhou

The analytical prediction of building energy performance in residential buildings based on the heat losses of its individual envelope components is a challenging task. It is worth noting that this field is still in its infancy, with…

Accurate short-term energy consumption forecasting is essential for efficient power grid management, resource allocation, and market stability. Traditional time-series models often fail to capture the complex, non-linear dependencies and…

Computers and Society · Computer Science 2026-01-27 Abhishek Maity , Viraj Tukarul

Load points are one of the most vital parts of power systems. Due to the new load forms and programs introduced in the demand side, the load-serving entities (LSEs) no longer deal with lump loads, but rather with more dynamic, rational and…

Systems and Control · Electrical Eng. & Systems 2021-10-13 Ahmed S. Alahmed , Muhammed M. Almuhaini

Electrified heating systems with thermal storage, such as electric boilers and heat pumps, represent a major source of demand-side flexibility. Under current electricity market designs, balance responsible parties (BRPs) operating such…

Systems and Control · Electrical Eng. & Systems 2026-02-20 Alessandro Quattrociocchi , Manisha Talukdar , Pere Izquierdo Gómez , Tomislav Dragicevic

Electricity consumption has increased exponentially during the past few decades. This increase is heavily burdening the electricity distributors. Therefore, predicting the future demand for electricity consumption will provide an upper hand…

Machine Learning · Computer Science 2019-09-19 Anupiya Nugaliyadde , Upeka Somaratne , Kok Wai Wong

This research provides an in-depth evaluation of various machine learning models for energy forecasting, focusing on the unique challenges of seasonal variations in student residential settings. The study assesses the performance of…

Machine Learning · Computer Science 2025-07-01 Muhammad Umair Danish , Mathumitha Sureshkumar , Tehara Fonseka , Umeshika Uthayakumar , Vinura Galwaduge

The rising availability of large volume data, along with increasing computing power, has enabled a wide application of statistical Machine Learning (ML) algorithms in the domains of Cyber-Physical Systems (CPS), Internet of Things (IoT) and…

Signal Processing · Electrical Eng. & Systems 2020-11-30 Yongchao Huang , Hugh Miles , Pengfei Zhang

In low-income settings, the most critical piece of information for electric utilities is the anticipated consumption of a customer. Electricity consumption assessment is difficult to do in settings where a significant fraction of households…

Computer Vision and Pattern Recognition · Computer Science 2021-12-17 Simone Fobi , Joel Mugyenyi , Nathaniel J. Williams , Vijay Modi , Jay Taneja

Integrating renewable energy sources into the power grid is becoming increasingly important as the world moves towards a more sustainable energy future in line with SDG 7. However, the intermittent nature of renewable energy sources can…

In coming years residential consumers will face real-time electricity tariffs with energy prices varying day to day, and effective energy saving will require automation - a recommender system, which learns consumer's preferences from her…

Machine Learning · Computer Science 2017-02-01 Mikhail V. Goubko , Sergey O. Kuznetsov , Alexey A. Neznanov , Dmitry I. Ignatov

Building heat electrification is central to economy-wide decarbonization efforts and directly affects energy infrastructure planning through increasing electricity demand and reducing the building sector's use of gas infrastructure that…

Systems and Control · Electrical Eng. & Systems 2024-09-17 Rahman Khorramfar , Morgan Santoni-Colvin , Saurabh Amin , Leslie K. Norford , Audun Botterud , Dharik Mallapragada

In the context of global warming, even relatively cooler countries like the UK are experiencing a rise in cooling demand, particularly in southern regions such as London. This growing demand, especially during the summer months, presents…

Physics and Society · Physics 2025-03-11 Meng Zhang , Zhihui Li , Zhibin Yu

The smart metering infrastructure has changed how electricity is measured in both residential and industrial application. The large amount of data collected by smart meter per day provides a huge potential for analytics to support the…

Machine Learning · Computer Science 2019-05-31 Nameer Al Khafaf , Mahdi Jalili , Peter Sokolowski

Electricity forecasting has been a recurring research topic, as it is key to finding the right balance between production and consumption. While most papers are focused on the national or regional scale, few are interested in the household…