[HTML][HTML] Role of input features in developing data-driven models for building thermal demand forecast

C Wang, X Li, H Li - Energy and Buildings, 2022 - Elsevier
The energy consumption of buildings accounts for a major share in the modern society.
Accurate forecast of building thermal demand is of great significance to both building …

[HTML][HTML] Opportunities for machine learning in district heating

G Mbiydzenyuy, S Nowaczyk, H Knutsson… - Applied Sciences, 2021 - mdpi.com
The district heating (DH) industry is facing an important transformation towards more efficient
networks that utilise significantly lower water temperatures to distribute the heat. This …

[HTML][HTML] Development of electricity consumption profiles of residential buildings based on smart meter data clustering

L Czétány, V Vámos, M Horváth, Z Szalay… - Energy and …, 2021 - Elsevier
In the present research, a high-resolution, detailed electric load dataset was assessed,
collected by smart meters from nearly a thousand households in Hungary, many of them …

Prioritizing urban planning factors on community energy performance based on GIS-informed building energy modeling

H Yu, M Wang, X Lin, H Guo, H Liu, Y Zhao, H Wang… - Energy and …, 2021 - Elsevier
The residential sector accounts for an increasing amount of global energy use with
continued urbanization. Residential energy-informed urban planning offers an economical …

Prediction and comparison of urban electricity consumption based on grey system theory: A case study of 30 southern China cities

M Wang, H Yu, R Jing, X Lin - Cities, 2023 - Elsevier
Rapid urbanization has put heavy pressure on urban energy supply over the past decades
in China and such a trend is expected to continue. Therefore, it is critical to capture the …

[HTML][HTML] Who Produces the Peaks? Household Variation in Peak Energy Demand for Space Heating and Domestic Hot Water

AR Hansen, D Leiria, H Johra… - Energies, 2022 - mdpi.com
Extensive research demonstrates the importance of user practices in understanding
variations in residential heating demand. Whereas previous studies have investigated …

Modeling occupancy-driven building loads for large and diversified building stocks through the use of parametric schedules

C Bianchi, L Zhang, D Goldwasser, A Parker, H Horsey - Applied Energy, 2020 - Elsevier
Building energy modeling provides a fundamental tool to evaluate the potential for energy
efficiency to contribute to reducing world energy consumption and global emissions …

Load pattern recognition based optimization method for energy flexibility in office buildings

Q Wang, Y Ding, X Kong, Z Tian, L Xu, Q He - Energy, 2022 - Elsevier
Air conditioning systems are generally considered to have the greatest flexibility potential in
buildings that can be flexibly regulated with thermal storage to reduce the interaction with …

Research on data-driven identification and prediction of heat response time of urban centralized heating system

W Zhong, W Huang, X Lin, Z Li, Y Zhou - Energy, 2020 - Elsevier
Heat response time (HRT) is one of the key dynamic response characteristics of urban
centralized heating system (UCHS). HRT is also critical to the operation dispatch of large …

[HTML][HTML] Three years of hourly data from 3021 smart heat meters installed in Danish residential buildings

M Schaffer, T Tvedebrink, A Marszal-Pomianowska - Scientific Data, 2022 - nature.com
The now widespread use of smart heat meters for buildings connected to district heating
networks generates data at an unknown extent and temporal resolution. This data …