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A National Heat Demand Model for Germany

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Agent Based Modelling of Urban Systems (ABMUS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10051))

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Abstract

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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Authors and Affiliations

  1. HafenCity University Hamburg, Überseealle 16, 20457, Hamburg, Germany

    Marcelo Esteban Muñoz Hidalgo

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  1. Marcelo Esteban Muñoz Hidalgo
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Correspondence to Marcelo Esteban Muñoz Hidalgo .

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Editors and Affiliations

  1. University of Wollongong , Wollongong, New South Wales, Australia

    Mohammad-Reza Namazi-Rad

  2. RMIT University , Melbourne, Victoria, Australia

    Lin Padgham

  3. University of Wollongong , Wollongong, New South Wales, Australia

    Pascal Perez

  4. Technische Universität Berlin , Berlin, Germany

    Kai Nagel

  5. Universidade Federal do Rio Grande do Sul , Rio Grande do Sul, Brazil

    Ana Bazzan

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Muñoz Hidalgo, M.E. (2017). A National Heat Demand Model for Germany. In: Namazi-Rad, MR., Padgham, L., Perez, P., Nagel, K., Bazzan, A. (eds) Agent Based Modelling of Urban Systems. ABMUS 2016. Lecture Notes in Computer Science(), vol 10051. Springer, Cham. https://doi.org/10.1007/978-3-319-51957-9_10

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  • DOI: https://doi.org/10.1007/978-3-319-51957-9_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-51956-2

  • Online ISBN: 978-3-319-51957-9

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