Collaborative Energy and Comfort Management Through Distributed Consensus Algorithms

Abstract—Buildings with shared spaces such as corporate office buildings, university dorms, etc. are occupied by multiple occupants who typically have different temperature preferences. Attaining a common temperature set-point that is agreeable to all users (occupants) in such a multi-occupant space is a challenging problem. Furthermore, the ideal temperature set-point should optimally trade off the building energy cost with the aggregate discomfort of all the occupants. However, the information on the comfort range (function) is held privately by each occupant. Using occupant-differentiated dynamically-adjusted prices as feedback signals, we propose a distributed solution which ensures that a consensus is attained among all occupants upon convergence, irrespective of their ideal temperature preferences being in coherence or conflicting. Occupants are only assumed to be rational, in that they choose their own temperature set-points so as to minimize their individual energy cost plus discomfort. We establish the convergence of the proposed algorithm to the optimal temperature set-point vector that minimizes the sum of the energy cost and the aggregate discomfort of all occupants in a multi-zone building. Simulations with realistic parameter settings illustrate validation of our theoretical claims and provide insights on the dynamics of the system with a mobile user population.