Reinforcement learning for building controls: The opportunities and challenges
Building controls are becoming more important and complicated due to the dynamic and
stochastic energy demand, on-site intermittent energy supply, as well as energy storage …
stochastic energy demand, on-site intermittent energy supply, as well as energy storage …
[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] 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 …
A survey on model-based reinforcement learning
Reinforcement learning (RL) interacts with the environment to solve sequential decision-
making problems via a trial-and-error approach. Errors are always undesirable in real-world …
making problems via a trial-and-error approach. Errors are always undesirable in real-world …
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 …