Calibration methodology for combined heating and ventilation models

By 2050, Europe aims for energy-neutral buildings, necessitating effective integration of renewable energy sources and smart grid management. To address peak energy demands and prevent grid congestion, building-level energy management is crucial. This paper presents a stepwise calibration methodology for hybrid building models, enhancing flexibility in HVAC systems and thermal buffers.   
The methodology involves: (1) utilizing known building and installation data to reduce calibration parameters, (2) independently calibrating subsystems like floor heating and cooling, (3) selecting optimal time periods for parameter estimation based on different physical mechanisms, and (4) validating the model with actual measurements. 
The SirinE hybrid model combines physical and data-driven components, leveraging known building data to minimize the need for detailed measurements. Successfully applied in various projects, SirinE improves PV energy self-utilization and electrical energy demand.         
Future work will focus on automating calibration, enhancing model robustness against user behaviour and sensor failures, and refining the hybrid model for evaluating residential renovations in an open source version. This methodology supports efficient energy management and integration of renewable sources in the built environment.