Experimental estimation of building energy performance by robust regression

Estimation of energy performance indexes, like the heating curve or the energy signature, requires robust regression of the heating losses on the outdoor temperature. The solution proposed in this paper is to use the range between the 1st and the 3rd quartile of the quantile–quantile (q–q) plot to check if the heating losses and the outdoor temperature have the same distribution and, if yes, to perform the regression in this range of the q–q plot. The result is a model that conserves its prediction performance for data sets of the outdoor temperature different of those used for parameter identification. The robust model gives the overall heat transfer coefficient and the base temperature, and it may be used to estimate the energy consumption for data sets of the outdoor temperature coming from different time—space locations.