Human-in-the-loop Thermal Management for Smart Buildings

Most of the current studies and solutions developed for building thermal control have been designed independent of the occupant feedback. An acceptable temperature range for the occupancy level is estimated, and control input is designed to maintain temperature within that range during occupancy hours. Consider office floors with cubicles, conference rooms, student dorms, homes, and other multi-occupant spaces where temperature set-points on thermostats are chosen irrespective of the number of occupants and their individual preferences. This existing approach is not only non user-centric but also sub-optimal from both energy consumption and occupant satisfaction/productivity perspectives. It is thus highly desirable for such multi-occupant spaces to have a mechanism that would take into account each occupants individual comfort preference and the energy cost, to come up with optimal thermal setting. Individual occupants feedback and preference can be obtained through wearable sensors or smart phone applications. In this chapter we propose algorithms that take into account each occupants preferences along with the thermal correlations between different zones in a building, to arrive at optimal thermal settings for all zones of the building in a coordinated manner. First, we present a control algorithm that uses binary occupant feedback based on singular perturbation theory to minimize aggregate user discomfort and total energy cost. A consensus algorithm for attaining a common temperature set-point in a typical multi-occupant space is presented next that uses Alternating Direction Method of Multipliers (ADMM) to solve the consensus problem. We use our Watervliet, NY based test facility to simulate the performance of our algorithms. Santosh K. Gupta ECSE Dept., Rensselaer Polytechnic Institute, e-mail: [email protected] Koushik Kar ECSE Dept., Rensselaer Polytechnic Institute e-mail: [email protected]