Conference Paper

Proceedings of BSA Conference 2017: Third Conference of IBPSA-Italy

Calibration of the Energy Simulation Models using Tikhonov-Type Regularization: Application to a Residential Building Apartment

Maja Miletić, Chiara Dipasquale, Roberto Fedrizzi

Abstract: It is well known that the calibration of building energy models is an under-determined problem, whether subjected to hourly or monthly calibration criteria. In fact, while it is possible to identify a large number of calibrated models, it is not clear which offer a good representation of the building behaviour. For a calibration methodology of building energy models to be effective, it should automate and speed-up calibration processes. This is especially important when the number of model parameters is too large to tune manually. Moreover, when the number of model parameters is too large, the probability to find the real parameter combination using statistical sampling methods is very small. Instead, we suggest performing a guided search of the parameter space, e.g. solving a parameter optimization problem. Since Tikhonov-type regularization has been applied successfully to many ill-posed inverse problems, we propose adopting the same methodology to find optimal parameters for building energy models. The regularization term can be interpreted as imposing certain a-priori distributions on model parameters as identified by an energy audit. As an illustration, the study case of a residential apartment is calibrated and we show that regularization more accurately predicts the energy demand estimate after the retrofit of the study case.
Pages: 175 - 184
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