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] Data-driven predictive control for unlocking building energy flexibility: A review
Managing supply and demand in the electricity grid is becoming more challenging due to
the increasing penetration of variable renewable energy sources. As significant end-use …
the increasing penetration of variable renewable energy sources. As significant end-use …
[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 …
Model predictive control (MPC) for enhancing building and HVAC system energy efficiency: Problem formulation, applications and opportunities
In the last few years, the application of Model Predictive Control (MPC) for energy
management in buildings has received significant attention from the research community …
management in buildings has received significant attention from the research community …
Ten questions concerning model predictive control for energy efficient buildings
Buildings are dynamical systems with several control challenges: large storage capacities,
switching aggregates, technical and thermal constraints, and internal and external …
switching aggregates, technical and thermal constraints, and internal and external …
Comprehensive analysis of the relationship between thermal comfort and building control research-A data-driven literature review
Buildings are responsible for about 30–40% of global energy demand. At the same time, we
humans spend almost our entire life, up to 80–90% of the time, inside of buildings. Reducing …
humans spend almost our entire life, up to 80–90% of the time, inside of buildings. Reducing …
Deep reinforcement learning to optimise indoor temperature control and heating energy consumption in buildings
Abstract In this work, Deep Reinforcement Learning (DRL) is implemented to control the
supply water temperature setpoint to terminal units of a heating system. The experiment was …
supply water temperature setpoint to terminal units of a heating system. The experiment was …
[HTML][HTML] Approximate model predictive building control via machine learning
Many studies have proven that the building sector can significantly benefit from replacing the
current practice rule-based controllers (RBC) by more advanced control strategies like …
current practice rule-based controllers (RBC) by more advanced control strategies like …
Building thermal modeling and model predictive control with physically consistent deep learning for decarbonization and energy optimization
Being a primary contributor to global energy consumption and energy-related carbon
emissions, the building and building construction sectors are a crucial player in the …
emissions, the building and building construction sectors are a crucial player in the …
A review on the basics of building energy estimation
N Fumo - Renewable and sustainable energy reviews, 2014 - Elsevier
Energy security, environmental concerns, thermal comfort, and economic matters are driving
factors for the development of research on reducing energy consumption and the associated …
factors for the development of research on reducing energy consumption and the associated …