M. Sama, J. Arias
This work aims to study the thermal behavior of residential buildings by
using the data provided by smart thermostats and weather forecast data. For
this, we consider an equivalent ODE circuit model depending on four parameters
related to the heater power, the solar energy, heat capacity, and the thermal
resistance of the building. We consider a deterministic and a random version of
the model to overcome natural model uncertainty.Using a discretization adapted
to the given data, we derive discrete formulas for the deterministic identification
model and compute the main statistical moments of the random model. We
present an algorithm in order to simulate the temperature on a test dataset
by solving the random model. Algorithm is tested on real data from residential
buildings.
Palabras clave: thermal building models, ODE parameter estimation, uncertainty quantification, Internet of Things
Programado
GT11 Optimización Continua IV
10 de junio de 2022 10:10
A12
