Building energy prediction models and related uncertainties: A review
Building energy usage has been an important issue in recent decades, and energy
prediction models are important tools for analysing this problem. This study provides a …
prediction models are important tools for analysing this problem. This study provides a …
Energy modeling and model predictive control for HVAC in buildings: A review of current research trends
Buildings use up to 40% of the global primary energy and 30% of global greenhouse gas
emissions, which may significantly impact climate change. Heating, ventilation, and air …
emissions, which may significantly impact climate change. Heating, ventilation, and air …
[HTML][HTML] Explainable district heat load forecasting with active deep learning
District heat load forecasting is a challenging task that involves predicting future heat
demand based on historical data and various influencing factors. Accurate forecasting is …
demand based on historical data and various influencing factors. Accurate forecasting is …
[HTML][HTML] Fifty shades of grey: Automated stochastic model identification of building heat dynamics
To reach the carbon emission reduction targets set by the European Union, the building
sector has embraced multiple strategies such as building retrofit, demand side management …
sector has embraced multiple strategies such as building retrofit, demand side management …
Application of a large smart thermostat dataset for model calibration and Model Predictive Control implementation in the residential sector
Electrification of space heating combined with electricity generation through renewable
resources has a significant potential to reduce greenhouse gas emissions, especially when …
resources has a significant potential to reduce greenhouse gas emissions, especially when …
Thermal modeling for control applications of 60,000 homes in North America using smart thermostat data
As smart thermostats become increasingly available in residential buildings, there is an
opportunity to use measured building data to calibrate models for community and district …
opportunity to use measured building data to calibrate models for community and district …
Full-response model of transient heat transfer of building walls using thermoelectric analogy method
J Duan, N Li, J Peng, C Wang, Q Liu - Journal of Building Engineering, 2022 - Elsevier
The modeling calculation of heat transfer based on a resistance and capacitance network in
building systems is relatively complex. In this study, a full-response model of the thermal …
building systems is relatively complex. In this study, a full-response model of the thermal …
Diversity for transfer in learning-based control of buildings
The application of reinforcement learning to the optimal control of building systems has
gained traction in recent years as it can cut the building energy consumption and improve …
gained traction in recent years as it can cut the building energy consumption and improve …
Efficacy of temporal and spatial abstraction for training accurate machine learning models: A case study in smart thermostats
Smart thermostats are increasingly popular in homes and buildings as they improve
occupant comfort, lower energy use in heating and cooling systems, and reduce utility bills …
occupant comfort, lower energy use in heating and cooling systems, and reduce utility bills …
Performance analysis and comparison of data-driven models for predicting indoor temperature in multi-zone commercial buildings
Building thermal models, which characterize the properties of a building's envelope and
thermal mass, are essential for accurate indoor temperature and cooling/heating demand …
thermal mass, are essential for accurate indoor temperature and cooling/heating demand …