Model Predictive Control and energy optimisation in residential building with electric underfloor heating system

This work is concerned with modelling, Model Predictive Control (MPC) and on-line energy optimisation of a residential building in which an underfloor heating system based on electric heating foils is used. At first, the first-principle model is developed to determine air temperature inside the building. Low-order linear models for MPC are found. Tuning of MPC is discussed, both set-point change and disturbance compensation cases are discussed. Next, two control system structures are considered: MPC with a constant temperature set-point and MPC cooperating with a set-point optimiser which repeatedly calculates on-line the set-point in order to minimise the amount of energy used. Effectiveness of these structures is validated in simulations using a real scenario of outdoor temperature changes. In the first structure a natural method to reduce energy used is to slightly reduce the temperature set-point, e.g. reduction of the set-point from 21∘C to 18.5∘C leads to reducing the energy usage by approx. 1430 KWh during the heating season. Introduction of the set-point optimiser makes it possible to further reduce energy used by approx. 300 KWh annually. The presented solution is computationally efficient since in MPC and set-point optimisation the classical quadratic optimisation method is used on-line.