The paper presents the learnings from designing and running a model predictive control (MPC) of the heating system in a school building. Several real-life applications of MPC controlled heating have been presented in the literature. Most of them work by controlling the room temperature usingn a heating system and thus need a reference measured temperature in the building. Some have a single-zone temperature as the reference, while others use some kind of mean temperature of multiple rooms. In the present experiment, the MPC used the mean temperature of all rooms as the reference and was able to keep it within a lower and upper comfort bound, while minimizing the heat costs by responding to a heat price signal. However, the analyses of the temperature in each room revealed that the temperature bounds were heavily violated: some rooms were too cold and some too warm, while the mean was within the bounds. The main conclusion from the study is that, at least for buildings with different sized rooms and room radiator capacities, it’s not reliable to use a mean room temperature – rather, the control must consider individual rooms in order to guarantee comfort.