Conference Paper

Proceedings of Building Simulation 2019: 16th Conference of IBPSA

Energy Saving Potentials of a Centralized Hybrid Heating System via Adaptive Model Predictive Control in a Northern Italy Residential Building

Ettore Zanetti ¹, Rossano Scoccia ¹, Silvia Garone ², Marcello Aprile ¹, Mario Motta ¹, Livio Mazzarella ^1
1 Department of Energy, Politecnico di Milano, 20156 Milano, Italy
² Enersem, P.za Leonardo da Vinci, 32 – 20133 Milano

DOI: https://doi.org/10.26868/25222708.2019.210631
Abstract: Extensive research has been conducted on advanced control techniques for buildings in recent years. However, even though in theory and in few experimental studies, the benefit of advanced Building Energy Management Systems was shown in most newly built or renovated buildings a traditional approach is still preferred, due to the higher cost and complexity of more advanced approaches despite the benefits. This paper presents a Python-Modelica grey-box modelling and adaptive optimal control of a hybrid heating system coupled with a thermal storage, that aims to reduce costs and improve the performance by better exploiting the hybrid heating system and the thermal storage, within the project TEPORE. The results show that for the chosen case study there are not enough degrees of freedom for the hybrid heating system to be optimized. However, interesting results emerged from changing the heating capacity of the generators showing on average 50% reduction in running costs.
Keywords: Optimization, Adaptive Model Predictive Control, Hybrid heating system, heat pump, thermal storage
Pages: 2925 - 2932
Paper: