A National Heat Demand Model for Germany
Spatial microsimulation models can be used for the analysis of complex systems. In this paper we make use of a spatial microsimulation model for the estimation of heat demand for Germany at a NUTS–3 level. The presented model creates a synthetic building stock by re-weighting the national microdata...
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Published in | Agent Based Modelling of Urban Systems pp. 172 - 188 |
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Main Author | |
Format | Book Chapter |
Language | English |
Published |
Cham
Springer International Publishing
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Series | Lecture Notes in Computer Science |
Subjects | |
Online Access | Get full text |
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Summary: | Spatial microsimulation models can be used for the analysis of complex systems. In this paper we make use of a spatial microsimulation model for the estimation of heat demand for Germany at a NUTS–3 level. The presented model creates a synthetic building stock by re-weighting the national microdata sample to small areas (NUTS–3) statistics with help of the GREGWT algorithm. Using the GREGWT method we benchmark the microdata sample to three different aggregation units (a) the building level (i.e. number of buildings); (b) families/dwelling units; and (c) individuals.
The model takes into account the different climate regions defined on the national German 18599-DIN standard. In order to incorporate the climate data into the model, we make use of a quasi steady-state heat transfer model to compute the heat demand of the individual buildings. These type of models require a building geometry for the estimation of heat demand, in this case we do not have information of the individual building geometry but only about the building size, expressed as square meters. We define synthetic geometrical boxes for the computation of heat demand.
The described model is able to represent the national building stock at a microlevel. These type of models are essential for the assessment of policies targeting (a) the reduction of carbon emissions in the construction sector and (b) the increase of energy efficiency on heat distribution grids. |
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ISBN: | 3319519565 9783319519562 |
ISSN: | 0302-9743 1611-3349 |
DOI: | 10.1007/978-3-319-51957-9_10 |