@inbook{10498/38806,
year = {2019},
url = {http://hdl.handle.net/10498/38806},
abstract = {The methodology for district heating networks modeling and energy and exergy analysis, which was introduced in Chapter 5, is now applied to a real urban area located in the city of Vienna (Austria).
Throughout this chapter the case study is described, including important aspects about the design and operation of the Viennese district heating network in particular, as well as different configurations of heating and hot water installations inside the buildings. Control and instrumentation strategies are also considered.
Consequently, each scenario for this case study is explained, taking the current situation of the network and the buildings as the reference to compare with. After running the simulation for eight proposed scenarios, energy and exergy balance results are obtained, allowing to analyze the efficiency of the system for each scenario. This analysis provides a useful information before proceeding to any project involving changes or reforms at network or building level.
The assessment of long and short-term energy policies for the urban building stock requires the evaluation of energy use for a large number of buildings. When building energy modeling is utilized as part of this process, it is important to provide reliable energy models for scenario assessment of various energy conservation measures. Nevertheless, large-scale urban energy modeling is a complicated task involving different sources of uncertainties, which create gaps between metered and simulated consumption. This section presents an innovative method for district and urban scale building energy models calibration. The presented approach relies on 4 main modeling strategies: (i) the creation of a large-scale automatic building energy modeling approach; (ii) the use of results derived by clustering algorithms for building classification; (iii) the definition of a Bayesian calibration framework; (iv) the use of advanced data-driven modeling techniques acting as emulators of a dynamic simulation engine. The proposed approach is developed and tested using data from a district case study of the city of Geneva. Results show the ability of the proposed modeling framework to generate reliable results in terms of energy modeling and the importance of developing accurate emulators based on data-driven approaches to overcome computational burdens and to correctly map the dynamic behavior of the dynamic simulation engine. The key points of the section can be summarized as follows:
    • an automated urban scale building energy modeling approach allows the creation of multizone simulation models for a dynamic building simulation software using the 3D model of the city;
    • a large-scale calibration technique for urban building energy models is presented;
    • the calibration approach is based on the use of Bayesian theory and various emulators of the dynamic simulation software; and
    • results show high accuracy of the model when compared to state of the art techniques in the literature.},
publisher = {Elsevier},
title = {Applying modeling and optimization tools to existing city quarters},
doi = {10.1016/B978-0-12-811553-4.00010-X},
author = {Potente Prieto, Mario and Monsalvete Álvarez de Uribarri, María Del Pilar and Tardioli, Giovanni},
}