A novel spatiotemporal home heating controller design: System emulation and field testing

We have developed a spatiotemporal heating control algorithm for use in homes. This system utilises a combination of relatively low-tech hardware interfaced with electric heating systems and a smartphone interface to this hardware, and a central server that progressively learns users’ room-specific presence profiles and thermal preferences. This paper describes the associated spatiotemporal heating control algorithm, its evaluation utilising the dynamic building performance simulation software EnergyPlus, and a longitudinal deployment of the algorithm controlling a quasi-autonomous spatiotemporal home heating system in three domestic homes. In this we focus on the prediction of occupants’ presence and preferred set-point temperature as well as on the calculation of optimum start time and the utilisation of user-scheduled absences; this for two comfort strategies: to maximise comfort and to minimise discomfort. The former aims to deliver conditions equating to a ‘neutral’ thermal sensation, whereas the latter targets a ‘slightly cool’ sensation with corresponding heating energy savings. Simulation results confirmed that the algorithm functions as intended and that it is capable of reducing energy demand by a factor of seven compared with EnergyStar recommended settings for programmable thermostats. Field study results align with these findings and highlight the possibility to reduce energy under the minimise discomfort strategy without compromising on occupants’ thermal comfort.