Improving energy savings and thermal comfort in large-scale buildings via adaptive optimization

Nowadays, most energy savings and thermal comfort improvements in buildings rely on passive design and construction techniques like superinsulation, passive solar heat gain and shading. Despite the benefits of passive design, active techniques for Building Optimization and Control (BOC) can result in relevant energy savings in everyday buildings without the need for expensive investments associated with passive solutions. The essence of BOC algorithms lies in controlling the Heating, Ventilation, and Air Conditioning (HVAC) system of a building to manage energy demands and improve thermal comfort conditions for occupants. In order to develop efficient BOC systems two aspects that must be handled efficiently are the large-scale nonlinear nature of the optimization problem and the uncertainty in the dynamics of the building.