Transfer learning for smart buildings: A critical review of algorithms, applications, and future perspectives
Smart buildings play a crucial role toward decarbonizing society, as globally buildings emit
about one-third of greenhouse gases. In the last few years, machine learning has achieved …
about one-third of greenhouse gases. In the last few years, machine learning has achieved …
[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 …
[HTML][HTML] Reinforced model predictive control (RL-MPC) for building energy management
Buildings need advanced control for the efficient and climate-neutral use of their energy
systems. Model predictive control (MPC) and reinforcement learning (RL) arise as two …
systems. Model predictive control (MPC) and reinforcement learning (RL) arise as two …
Non-destructive techniques (NDT) for the diagnosis of heritage buildings: Traditional procedures and futures perspectives
It is estimated that EU cultural heritage (CH) buildings represent 30% of the total existing
stock. Nevertheless, all actions in terms of refurbishment need a deep knowledge based on …
stock. Nevertheless, all actions in terms of refurbishment need a deep knowledge based on …
Hybrid system controls of natural ventilation and HVAC in mixed-mode buildings: A comprehensive review
Mixed-mode buildings utilise a combination of natural ventilation from operable building
envelopes and mechanical systems to realise climate-friendly ventilation and cooling. The …
envelopes and mechanical systems to realise climate-friendly ventilation and cooling. The …
Sustainable building climate control with renewable energy sources using nonlinear model predictive control
Sustainable energy sources are promising solutions for reducing carbon footprint and
environmental impacts within the building sectors. Reducing energy consumption while …
environmental impacts within the building sectors. Reducing energy consumption while …
Field demonstration and implementation analysis of model predictive control in an office HVAC system
Abstract Model Predictive Control (MPC) is a promising technique to address growing needs
for heating, ventilation, and air-conditioning (HVAC) systems to operate more efficiently and …
for heating, ventilation, and air-conditioning (HVAC) systems to operate more efficiently and …
Online transfer learning strategy for enhancing the scalability and deployment of deep reinforcement learning control in smart buildings
In recent years, advanced control strategies based on Deep Reinforcement Learning (DRL)
proved to be effective in optimizing the management of integrated energy systems in …
proved to be effective in optimizing the management of integrated energy systems in …
[HTML][HTML] Advanced development and application of transcritical CO2 refrigeration and heat pump technology—A review
As a highly efficient thermodynamic cycle formed by pure natural fluid and using
aerothermal energy, transcritical CO 2 technology has huge advantages in terms of energy …
aerothermal energy, transcritical CO 2 technology has huge advantages in terms of energy …
Ten questions concerning reinforcement learning for building energy management
As buildings account for approximately 40% of global energy consumption and associated
greenhouse gas emissions, their role in decarbonizing the power grid is crucial. The …
greenhouse gas emissions, their role in decarbonizing the power grid is crucial. The …