Artifact for the paper "Towards Model-Driven Heat Pump Control in a Multi-Story Building"

This is a reproducibility package for the paper "Towards Model-Driven Heat Pump Control in a Multi-Story Building".

Domestic heating systems can provide significant energy flexibility when integrated with heat pumps and hot water buffer tanks, especially with fluctuating day-ahead energy prices. However, optimizing these systems in large buildings with shared resources poses crucial challenges. While most existing studies target single-room or single-family house systems, this study explores the complexities within a three-story building housing six apartments. The building’s heating system consists of a hot water buffer tank, mixing loop, radiant floor heating system, and a Ground Source Heat Pump (GSHP) controlled by a weather-compensated control strategy (WCS). Our approach aims to tackle challenges like integrating real sensor data, scalability, varying weather effects, and diverse resident heat use preferences. We employ the CTSMR software to identify thermal behaviour and use reinforcement learning to design an intelligent/model-driven UPPAAL STRATEGOcontroller. Our results reveal a 43% reduction in energy costs while maintaining comfort levels compared to a WCS. The temporal validity of the estimated thermal models is also analyzed.