Laboratory test of commercial smart radiator thermostats when used for load shifting
Keywords:Smart thermostats, thermostat performance, load shifting, Model Predictive Control
The recent development of smart radiator thermostats has made it possible to integrate them in demand response programs. Advanced control strategies for demand response such as Model Predictive control (MPC) can be combined with radiator thermostats in a hierarchical way for the regulation of space heating systems: the MPC controller calculates the optimal set-point temperature to be tracked by the PID controller of the thermostat. Coupling MPC and thermostat-based control gives the possibility to regulate independently each radiator flow and therefore has the advantage of an efficient room temperature control. Currently, several smart thermostats available on the market are programmable, can be controlled remotely and allow to implement advanced control algorithms. In addition, the thermostats used for load shifting should be reliable, fast responding to changes in settings and precise in tracking a room temperature set-point. The purpose of this study was to compare the performance of different commercial smart radiator thermostats by performing laboratory experiments and to evaluate whether they are appropriate for load shifting purposes. The thermostats tested were Danfoss Eco 2, Eurotronic Spirit Z-Wave Plus and MClimate Vicki. The experiments were carried out in a room where the temperatures in strategic locations were measured. The experiments were designed to evaluate how the thermostats reacted to a changed set-point and if they were able to maintain the desired room temperature. Additionally, the experiments assessed how an increasing temperature set-point affected the flow, the radiator cooling and the thermal comfort in proximity to the radiator. The results obtained so far show that the three tested thermostats had different behaviours in terms of temperature control reliability and accuracy. The three products had different advantages and drawbacks and they all require adjustments for successful integration in an MPC system.
How to Cite
This work is licensed under a Creative Commons Attribution 4.0 International License.