Abstract
Building energy modelling and simulations play an important role in the design of energy efficient buildings but also in post-construction phases for commissioning, operation and optimization. With the use of data from monitoring systems related to the operation conditions of a building, calibrated simulations can be performed that accurately follow the real energy performance of a building. This paper present a procedure to achieve a calibrated building energy model simulation using monitoring data. The aim of the study is to verify/validate the results of the building energy model simulation against measured data. The study is based on an existing highly energy efficient building, which is continuously monitored in terms of energy consumptions and environmental parameters for several years now. The performance of the building energy model was assessed using statistical indices. The monthly total energy consumption comparison between simulated and measured shows that the building energy model managed to predict very closely the measured values. The accuracy of the building energy model in predicting air temperature was assessed as well.
Highlights
Building energy modelling (BEM) is an important process towards the design and optimization of buildings energy performance
The Normalized Mean Bias Error (NMBE) and CVRMSE values of -1.11% and 3.84% for total energy consumption are within the acceptance limit of ±5% and 15%
The CVRMSE gives an overall evaluation of the difference between the measured and simulated values while the NMBE characterizes the bias of the difference
Summary
Building energy modelling (BEM) is an important process towards the design and optimization of buildings energy performance. The complexity of a building when it comes to creating a building energy model comes from the multitude of parameters including material properties, infiltration, uncontrolled ventilation, HVAC specifications and operation, occupancy schedules, temperature set points, equipment and lighting schedules, weather etc. All these parameters are vast sources of uncertainty in building modelling [1], which can be responsible for gaps between the simulated and real energy performance of a building and makes necessary the process of calibration. This paper follows the development of a building energy model towards a calibrated simulation for an existing residential building for which monitoring data is available
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