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Abstract
An urban energy management tool was developed, which is able to predict the heating energy demand of urban districts and analyze strategies for improving building standards. Building models of different Levels of Detail are investigated and analyzed according to their suitability for forecasting energy demand. Based on the specific 3D city model, an input file is generated, which can be read by the building simulation model. Special focus is put on a method for modeling the heating energy demand of the buildings with the fewest input parameters possible, but one which will give reliable forecast results. A simple transmission heat loss method and an energy-balance method were tested. In both cases, there was a good correlation between the measured and calculated annual values for a case study area of over 700 buildings in Ostfildern, Germany. The results also show that a 3D city model (with low geometrical detail) can be used for energy demand forecasting on an urban scale.
Acknowledgments
The authors would like to thank the LANDESSTIFTUNG Baden-Württemberg (Project: Energy Efficient Cities) and the EU-Project POLYCITY (REF EC: TREN/05FP6EN/S07.43964/513481/) for funding part of this research. The authors would like to thank Hugo Ledoux and Martijn Maijers from TU Delft for their help generating the topologically correct 3D city model. Special thanks also to Martin Huber (from zafh.net) for his help with the automated transfer of the heating energy consumption data via the M-bus data logger and also to Dirk Pietruschka and Jürgen Schumacher (from zafh.net) for the technical support with the INSEL-simulation model. The authors would like to acknowledge financial support of the CITYNET project funded via the Marie Curie Research Training Network. This project financed the presentation of this article at the IAQVEC 2010 conference in Syracuse.
Aneta Strzalka is PhD Student and Researcher. Jürgen Bogdahn is PhD Student and Researcher. Volker Coors is Professor. Ursula Eicker is Professor and Scientific Director.