An Inferential Model-Based Predictive Control Scheme for Optimizing the Operation of Boilers in Building Space-Heating Systems

An inferential model-based predictive control scheme is described that can optimize the control of boilers in multi-zone heating systems in order to save energy and to improve thermal comfort. The controller has only three inputs: a measurement of the outside air temperature, an estimate of the total solar radiation falling on the exterior of the building, and a measurement of the temperature of the water being supplied by the boiler, and one output: the boiler control signal. The parameters of the model are estimated from input-output data collected using portable temperature loggers, which are temporarily installed in the building to monitor the room temperatures during a short commissioning period of one or two weeks. The performance of the control scheme in different heating systems is investigated using a heating system simulator, which had been developed and validated in previous projects. The simulation results show that the control scheme can significantly improve the overall performance of heating systems compared with conventional boiler control schemes and is easy to commission. The results of an experimental evaluation of the controller in a real building are also presented.