A national heat demand model for Germany

Marcelo Esteban Munoz Hidalgo

doi:10.1007/978-3-319-51957-9_10

A national heat demand model for Germany

Marcelo Esteban Munoz Hidalgo^*

^*Corresponding author for this work

Smart Building Engineering

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.

Original language	English
Title of host publication	Agent Based Modelling of Urban Systems - 1st International Workshop, ABMUS 2016 Held in Conjunction with AAMAS 2016, Revised, Selected, and Invited Papers
Editors	Ana Bazzan, Lin Padgham, Kai Nagel, Mohammad-Reza Namazi-Rad, Pascal Perez
Pages	172-188
Number of pages	17
ISBN (Electronic)	978-3-319-51957-9
DOIs	https://doi.org/10.1007/978-3-319-51957-9_10
Publication status	Published - 11 Jan 2017
Event	1st International Workshop on Agent Based Modelling of Urban Systems, ABMUS 2016 Held in Conjunction with Autonomous Agents and Multi Agent Systems, AAMAS 2016 - Singapore, Singapore Duration: 10 May 2016 → 10 May 2016

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer International Publishing
Number	10051
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	1st International Workshop on Agent Based Modelling of Urban Systems, ABMUS 2016 Held in Conjunction with Autonomous Agents and Multi Agent Systems, AAMAS 2016
Country/Territory	Singapore
City	Singapore
Period	10/05/16 → 10/05/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 07 Affordable and Clean Energy
SDG 13 Climate Action

Free Keywords

GREGWT
Heat demand
Synthetic building stock
Spatial microsimulation

Access to Document

10.1007/978-3-319-51957-9_10

Cite this

Munoz Hidalgo, M. E. (2017). A national heat demand model for Germany. In A. Bazzan, L. Padgham, K. Nagel, M.-R. Namazi-Rad, & P. Perez (Eds.), Agent Based Modelling of Urban Systems - 1st International Workshop, ABMUS 2016 Held in Conjunction with AAMAS 2016, Revised, Selected, and Invited Papers (pp. 172-188). (Lecture Notes in Computer Science; No. 10051). https://doi.org/10.1007/978-3-319-51957-9_10

Munoz Hidalgo, Marcelo Esteban. / A national heat demand model for Germany. Agent Based Modelling of Urban Systems - 1st International Workshop, ABMUS 2016 Held in Conjunction with AAMAS 2016, Revised, Selected, and Invited Papers. editor / Ana Bazzan ; Lin Padgham ; Kai Nagel ; Mohammad-Reza Namazi-Rad ; Pascal Perez. 2017. pp. 172-188 (Lecture Notes in Computer Science; 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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Munoz Hidalgo, ME 2017, A national heat demand model for Germany. in A Bazzan, L Padgham, K Nagel, M-R Namazi-Rad & P Perez (eds), Agent Based Modelling of Urban Systems - 1st International Workshop, ABMUS 2016 Held in Conjunction with AAMAS 2016, Revised, Selected, and Invited Papers. Lecture Notes in Computer Science, no. 10051, pp. 172-188, 1st International Workshop on Agent Based Modelling of Urban Systems, ABMUS 2016 Held in Conjunction with Autonomous Agents and Multi Agent Systems, AAMAS 2016, Singapore, Singapore, 10/05/16. https://doi.org/10.1007/978-3-319-51957-9_10

A national heat demand model for Germany. / Munoz Hidalgo, Marcelo Esteban.
Agent Based Modelling of Urban Systems - 1st International Workshop, ABMUS 2016 Held in Conjunction with AAMAS 2016, Revised, Selected, and Invited Papers. ed. / Ana Bazzan; Lin Padgham; Kai Nagel; Mohammad-Reza Namazi-Rad; Pascal Perez. 2017. p. 172-188 (Lecture Notes in Computer Science; No. 10051).

Research output: Chapter in Book (Inbook) /Conference Proceeding › Conference Paper › Research Article/Contribution › peer-reviewed

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N2 - 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.

AB - 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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BT - Agent Based Modelling of Urban Systems - 1st International Workshop, ABMUS 2016 Held in Conjunction with AAMAS 2016, Revised, Selected, and Invited Papers

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A2 - Namazi-Rad, Mohammad-Reza

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Munoz Hidalgo ME. A national heat demand model for Germany. In Bazzan A, Padgham L, Nagel K, Namazi-Rad MR, Perez P, editors, Agent Based Modelling of Urban Systems - 1st International Workshop, ABMUS 2016 Held in Conjunction with AAMAS 2016, Revised, Selected, and Invited Papers. 2017. p. 172-188. (Lecture Notes in Computer Science; 10051). doi: 10.1007/978-3-319-51957-9_10

A national heat demand model for Germany

Abstract

Publication series

Conference

UN SDGs

Free Keywords

Access to Document

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