All you need to know about model predictive control for buildings
It has been proven that advanced building control, like model predictive control (MPC), can
notably reduce the energy use and mitigate greenhouse gas emissions. However, despite …
notably reduce the energy use and mitigate greenhouse gas emissions. However, despite …
[HTML][HTML] Energy modelling and control of building heating and cooling systems with data-driven and hybrid models—A review
Implementing an efficient control strategy for heating, ventilation, and air conditioning
(HVAC) systems can lead to improvements in both energy efficiency and thermal …
(HVAC) systems can lead to improvements in both energy efficiency and thermal …
Physics-constrained deep learning of multi-zone building thermal dynamics
We present a physics-constrained deep learning method to develop control-oriented models
of building thermal dynamics. The proposed method uses systematic encoding of physics …
of building thermal dynamics. The proposed method uses systematic encoding of physics …
Development of energy aggregators for virtual communities: The energy efficiency-flexibility nexus for demand response
The implementation of load management and demand response programs is motivating
utilities to propose demand-side management to incentivize customers to modify their …
utilities to propose demand-side management to incentivize customers to modify their …
[HTML][HTML] Evaluation of advanced control strategies for building energy systems
Advanced building control strategies like model predictive control and reinforcement
learning can consider forecasts for weather, occupancy, and energy prices. Combined with …
learning can consider forecasts for weather, occupancy, and energy prices. Combined with …
Short-term cooling and heating loads forecasting of building district energy system based on data-driven models
H Yu, F Zhong, Y Du, Y Wang, X Zhang, S Huang - Energy and Buildings, 2023 - Elsevier
Accurate forecasting of cooling and heating loads is critical for optimizing the energy usage
of devices and planning for energy storage in building district energy systems (BDESs). Data …
of devices and planning for energy storage in building district energy systems (BDESs). Data …
A digital twin architecture for real-time and offline high granularity analysis in smart buildings
L Hadjidemetriou, N Stylianidis, D Englezos… - Sustainable Cities and …, 2023 - Elsevier
Smart buildings aim to create a safe, comfortable and sustainable environment for the
occupants while increasing the energy performance of the building to reduce the …
occupants while increasing the energy performance of the building to reduce the …
A digital twin framework for improving energy efficiency and occupant comfort in public and commercial buildings
Abstract Model Predictive Control (MPC) can be used in the context of building automation
to improve energy efficiency and occupant comfort. Ideally, the MPC algorithm should …
to improve energy efficiency and occupant comfort. Ideally, the MPC algorithm should …
Electrification-driven circular economy with machine learning-based multi-scale and cross-scale modelling approach
Community energy systems, integrating electricity storage, smart transportation, and flexible
energy interactions can mitigate renewable energy intermittency and uncertainty, and …
energy interactions can mitigate renewable energy intermittency and uncertainty, and …
[HTML][HTML] Safe operation of online learning data driven model predictive control of building energy systems
Abstract Model predictive control is a promising approach to reduce the CO 2 emissions in
the building sector. However, the vast modeling effort hampers the widescale practical …
the building sector. However, the vast modeling effort hampers the widescale practical …