Bottom-up modeling of the Belgian residential building stock: influence of model complexity

Abstract

Demand-side management using the thermal storage capacity of buildings is often suggested as an efficient and economically feasible technology to enable a wide-spread integration of intermittent renewable energy sources. Nevertheless, to quantify the potential benefits of activating the structural storage capacity on a national level, a dynamic bottom-up building stock model is needed. Thereby the aim is not only on the calculation of the annual heat demand, but mostly on an accurate dynamic simulation of the instantaneous heat demand and the indoor temperature, since these are directly linked to active demand response measures. In this paper the suitability of reduced-order models for the application in a dynamic bottom-up building stock model for Belgium is evaluated. Thereby a detailed building energy simulation is compared to reduced-order models of increasing complexity. For the latter both a theoretical approach and a parameter estimation method are analyzed. The building stock description is based on the typical housing approach of the TABULA-project. The reduced-order models show an acceptable prediction of the dynamic temperature profile and heat demand during the heating season, whilst reducing the calculation time significantly. Nevertheless, the reduced-order models are, due to the strong simplifications, less accurate when applied on boundary conditions which significantly differ from the identification data. Especially the coupling between two adjacent rooms is found to reduce the identifiability of the model parameters, resulting in unreliable estimates of inter-zonal heat flows.status: publishe