Energy Saving Recommendations and User Location Modeling in Commercial Buildings

Commercial buildings consume a large portion of the total electricity in the United States. One method for energy saving in commercial buildings targets inefficiencies of unoccupied spaces by relaxing the setpoint temperature. However, energy savings are severely limited when occupants are assumed to be "immovable objects"; instead, by encouraging occupant participation in the optimization, a much greater amount of energy savings can be achieved. In this work, we build on this idea and introduce energy saving recommendations based on occupant location. We introduce two types of energy saving recommendations based on location: move recommendations, which recommends the occupant to move from one space to another, and shift schedule recommendations, which recommends the occupant to arrive or depart a set amount of time earlier or later. To investigate the effects of the energy saving recommendations, we introduced a tightly coupled system composing of a simulator and a recommender system. Simulations in our building testbed revealed that energy saving recommendations coupled with occupancy-based HVAC energy management saves 25% more energy than occupancy-based HVAC energy management alone.