V utorok 21.5.2019 sa uskutočnil vedecký seminár, ktorý viedol náš úspešný absolvent Ing. Ján Drgoňa, PhD. (KU Lueven, Belgicko), na tému "Implementation and Remote Operation of White-Box Model Predictive Control in an Office Building".

FB-Udalosť     FB-Fotka

Abstract:

Model predictive control (MPC) has been proved in simulations and pilot case studies to be superior control strategy for large buildings. MPC can anticipate and utilize the weather and occupancy schedule forecasts, together with the system model to predict the future thermal behavior of the building and minimize the overall energy use and maximize thermal comfort. These advantages come with the cost of increased modeling costs, computational demands, communication infrastructure and expertise requirements on the commissioning staff. Implementation of MPC in real buildings, therefore, remains a challenge. This work presents a methodology and tutorial of MPC implementation in a large office building in Belgium equipped with ground source heat pump (GSHP) and thermally activated building structures (TABS), where a combination of both is also known as GEOTABS. From a control perspective, GEOTABS buildings are challenging systems due to large scale, complex heating ventilation and air conditioning (HVAC) systems, and slow dynamics. On the other hand, there is an increased potential for energy savings due to high thermal mass and seasonal thermal storage. The presented white-box MPC approach is based on a detailed physical model of the building with high prediction accuracy, allowing to leverage the full operational potential of GEOTABS building. The MPC is compared with traditional rule-based controller (RBC) on several weeks of operation in the heating and transient season. During the whole operation, MPC kept the zone operative temperatures closer to comfort bounds. Additionally, MPC decreased the supply temperature and operation time of the GSHP, resulting in a significant decrease in energy consumption of the GSHP with 66% energy savings in the heating season.