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 …
CNN-LSTM architecture for predictive indoor temperature modeling
Indoor temperature modeling is a crucial part towards efficient Heating, Ventilation and Air
Conditioning (HVAC) systems. Data-driven black-box approaches have been an attractive …
Conditioning (HVAC) systems. Data-driven black-box approaches have been an attractive …
Artificial neural network (ANN) based model predictive control (MPC) and optimization of HVAC systems: A state of the art review and case study of a residential HVAC …
In this paper, a comprehensive review of the artificial neural network (ANN) based model
predictive control (MPC) system design is carried out followed by a case study in which ANN …
predictive control (MPC) system design is carried out followed by a case study in which ANN …
Modeling techniques used in building HVAC control systems: A review
The appropriate application of advanced control strategies in Heating, Ventilation, and Air-
conditioning (HVAC) systems is key to improving the energy efficiency of buildings …
conditioning (HVAC) systems is key to improving the energy efficiency of buildings …
Deep reinforcement learning optimal control strategy for temperature setpoint real-time reset in multi-zone building HVAC system
X Fang, G Gong, G Li, L Chun, P Peng, W Li… - Applied Thermal …, 2022 - Elsevier
Determining a proper trade-off between energy consumption and indoor thermal comfort is
important for HVAC system control. Deep Q-learning (DQN) based multi-objective optimal …
important for HVAC system control. Deep Q-learning (DQN) based multi-objective optimal …
A comprehensive review: Fault detection, diagnostics, prognostics, and fault modeling in HVAC systems
This review study examines the latest research and developments in the fault detection and
diagnostics of Heating Ventilation and Air Conditioning (HVAC) systems. This review …
diagnostics of Heating Ventilation and Air Conditioning (HVAC) systems. This review …
[HTML][HTML] Transfer learning in demand response: A review of algorithms for data-efficient modelling and control
A number of decarbonization scenarios for the energy sector are built on simultaneous
electrification of energy demand, and decarbonization of electricity generation through …
electrification of energy demand, and decarbonization of electricity generation through …
A hybrid method of cooling load forecasting for large commercial building based on extreme learning machine
Z Gao, J Yu, A Zhao, Q Hu, S Yang - Energy, 2022 - Elsevier
Air conditioning system is extensively used in large commercial buildings. The fast and
accurate building cooling load forecasting is the basis for improving the operation efficiency …
accurate building cooling load forecasting is the basis for improving the operation efficiency …
Data requirements and performance evaluation of model predictive control in buildings: A modeling perspective
Abstract Model predictive control (MPC) has shown great potential in improving building
performance and saving energy. However, after over 20 years of research, it is yet to be …
performance and saving energy. However, after over 20 years of research, it is yet to be …