RT Dissertation/Thesis
T1 Research and development of automated calibration and multi-objective optimization techniques applied to simulation of building energy models
T2 Investigación y desarrollo de técnicas automatizadas de calibración y optimización multiobjetivo aplicadas a la simulación de modelos energéticos de edificios.
A1 Martinez Mariño, Sandra
K1 1203.26 Simulación
K1 3322.02 Generación de Energía
AB Buildings performance does not correspond to the predicted performance in the design phase. Several studies have revealed the discrepancies between the energy consumption of a simulated building and the measured consumption in the real building. The match between simulation models and measured data with monitoring should be improved, in order to have a reliable simulation tool. The improvement process is known as a model calibration.Calibrated model simulations are based on physical reality, real data from monitoring, rather than statistical or mathematical modifications, providing the ability to predict more accurate behaviour. The current problem is that there is no standard methodology, the uncertainty is high, and automated calibration tools are needed to simplify the process. Sensitivity analysis allows for detecting the parameters that have the greatest influence on the final response of the building model. Sensitivity analysis is necessary as a first step in the calibration process, orienting the parameter adjustment process to those that introduce the greatest error in the model.Once the most influential parameters of the model have been detected, they are calibrated with real monitoring data. The objective is to develop and implement calibration techniques that follow standardized, precise and reliable methods, that do not incur large costs, that take into account the uncertainty in the parameters and that can be automated. For these reasons, Bayesian calibration techniques and multi-objective optimization will be studied and implemented.Finally, multi-objective optimization can not only be used in the calibration of simulation models, but can also be applied to search for energy efficiency, involving diverse objectives that are in conflict and cannot be optimized simultaneously.
YR 2020
FD 2020-09-29
LK http://hdl.handle.net/11093/1556
UL http://hdl.handle.net/11093/1556
LA eng
DS Investigo
RD 22-sep-2023