Model predictive control of heating and cooling in a family house

The majority of energy, approximately 40% of total energy usage, is today spent in buildings. The largest energy consuming subsystem in a building is heating, ventilation and air conditioning (HVAC) system. In this work we focus on efficient energy usage for heating and cooling in a simple house that consists of three rooms. We use model predictive control to fully take into account the current thermal conditions in the house and the 24-hours-ahead weather forecast. The controller commands heating/cooling for rooms in the house such that the outdoor conditions are fully exploited in keeping the room temperatures within comfort limits and therefore minimum additional energy for heating/cooling is spent. In the work we first present the house model whose behaviour is verified in comparison with a detailed house model implemented in TRNSYS, and then for such model we derive a model predictive control strategy and verify it through simulations.