Publications in Scientific Journals:

P. Penna, F. Cappelletti, A. Gasparella, F. Tahmasebi, A. Mahdavi:
"Multi-Stage Calibration of the Simulation Model of a School Building through Short-Term Monitoring";
www.itcon.org - Journal of Information Technology in Construction, 20 (2015), Special Issue; 132 - 145.

English abstract:
The increasing attention on the improvement of new and existing buildings“ performance is
emphasizing the importance of the reliability of the simulation models in predicting the complexity of the
building behaviour and, consequently, in some advanced applications of building simulation, such as the
optimization of the choice of different Energy Efficiency Measures (EEMs) or the adoption of model predictive
control strategies. The reliability of the energy model does not depend only on the quality and details of the
model itself, but also on the uncertainty related to many input values, such as the physical properties of
materials and components, the information on the building management and occupation, and the boundary
conditions considered for the simulation. Especially for the existing buildings, this kind of data is often missing
or characterized by high uncertainty, and only very simplified behavioural models of occupancy are available.
This could compromise the optimization process and undermine the potential of building simulation. In this
context, the calibration of the simulation model by means of on-site monitoring is of crucial importance to
increase the reliability of the predictions, and to take better decisions, even though this process can be time
consuming. This work presents a multi-stage methodology to calibrate the building energy simulation by means
of low-cost monitoring and short-term measurements. This approach is applied to a Primary School in the
North-East of Italy, which has been monitored from December 2012 to April 2014. Four monitoring periods
have been selected to calibrate different sets of variables at a time, while the validation has been carried out on
two different periods. The results show that even if less than 8 weeks have been considered in the proposed
calibration approach, the maximum error in the estimation of the temperature is less than ±0.5 in 77.3% of the
timesteps in the validation period.

German abstract:
none - see english version

model calibration, energy simulation, optimization, monitoring

Created from the Publication Database of the Vienna University of Technology.