The paper introduces a hybrid modelling approach that enhances the accuracy and usability of physics-based energy simulation for existing buildings. The approach leverages measured zone air temperature data streams— increasingly available from smart thermostats—to derive difficult-to-obtain input parameters for internal thermal mass and infiltration airflow rates. It does so using a reformulated inverse heat balance algorithm. We implemented the inverse algorithms in EnergyPlus and used LBNL's Facility for Low Energy eXperiments (FLEXLAB) for demonstration and validation.
BT - Building Simulation 2017 CY - Building Simulation 2017 DA - 08/2017 DO - 10.26868/25222708.2017.137 LA - eng N2 -The paper introduces a hybrid modelling approach that enhances the accuracy and usability of physics-based energy simulation for existing buildings. The approach leverages measured zone air temperature data streams— increasingly available from smart thermostats—to derive difficult-to-obtain input parameters for internal thermal mass and infiltration airflow rates. It does so using a reformulated inverse heat balance algorithm. We implemented the inverse algorithms in EnergyPlus and used LBNL's Facility for Low Energy eXperiments (FLEXLAB) for demonstration and validation.
PB - IBPSA PP - Building Simulation 2017 PY - 2017 T2 - Building Simulation 2017 T3 - Building Simulation 2017 TI - Leveraging Zone Air Temperature Data to Improve Physics-Based Energy Simulation of Existing Buildings UR - https://doi.org/10.26868/25222708.2017.137 ER -