Reinforcement Learning

Towards self-adaptive building energy control in smart grids

We pursue to develop new Deep Learning and Reinforcement Learning methods, algorithms and tools to address three key issues -- generation of optimal control instructions for HVAC to save energy while guaranteeing comfort; simulation of buildings under different operations and contexts; coordination between components of the energy system to achieve an overall reduction of the contaminant emissions.