Field tests of an adaptive, model-predictive heating controller for residential buildings

Abstract Conventional weather-compensated heating controllers are often configured to deliver more heating than necessary, resulting in energy losses. Furthermore, they cannot take into account future climate conditions, and yield less than optimal thermal comfort. We have developed a non-invasive add-on module for existing heating controllers that implements an adaptive, model-predictive heating control algorithm. This algorithm helps the heating controller deliver a heating energy just sufficient for maintaining thermal comfort, resulting in energy savings. In this paper we report on the energy savings measured on ten buildings equipped with this device. By monitoring the space heating energy during the 2013–2014 heating season, and by periodically alternating between the new controller and the reference controller, we establish the energy signature of all buildings with both controllers. The comparison of the energy signatures yields the relative energy savings achievable with the new controller. These energy savings are positive for all test sites, with a mean of 28 ± 4% (standard error of the mean).