A Spatial Data Analysis Approach for Public Policy Simulation in Thermal Energy Transition Scenarios

Lina Stanzel; Johannes Scholz; Franz Mauthner

doi:10.1007/978-3-658-27495-5_8

A Spatial Data Analysis Approach for Public Policy Simulation in Thermal Energy Transition Scenarios

Lina Stanzel
, Johannes Scholz
, Franz Mauthner

Institute of Geodesy (5220)

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Abstract

The paper elaborates on an approach to simulate the effect of public policies regarding thermal energy transition pathways in urban communities. The paper discusses the underlying methodologies of calculating Heating Energy demand of buildings and the rationale for potential zones for thermal energy systems. In order to simulate the effects of public policies on communities the authors developed a spatial Agentbased Model, where the buildings are the main objects that are subject to change, based on a number of both technically and socio-demographic parameters. In order to fill a spatial Agentbased Model with data a number of open source and commercially available datasets need to be spatially analyzed and merged. The initial results of the spatial Agent-based Model simulation show that public policies for thermal energy transition can be simulated accordingly.

Original language	English
Title of host publication	Data Science - Analytics and Applications
Subtitle of host publication	Proceedings of the 2nd International Data Science Conference – iDSC2019
Editors	Peter Haber, Thomas Lampoltshammer, Manfred Mayr
Place of Publication	Wiesbaden
Publisher	Springer Vieweg
Pages	63-68
Number of pages	6
ISBN (Print)	978-3-658-27494-8
DOIs	https://doi.org/10.1007/978-3-658-27495-5_8
Publication status	Published - 2019
Event	2nd International Data Science Conference - Salzburg, Austria Duration: 22 May 2019 → 24 May 2019

Conference

Conference	2nd International Data Science Conference
Abbreviated title	iDSC2019
Country/Territory	Austria
City	Salzburg
Period	22/05/19 → 24/05/19

UN SDGs

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

SDG 7 Affordable and Clean Energy

Access to Document

10.1007/978-3-658-27495-5_8

ECC - EnergyCityConcepts: Methoden- und Konzeptentwicklung zur Implementierung nachhaltiger Energiesysteme in Städten am Beispiel von Gleisdorf und Salzburg
Edtmayer, H., Nageler, P. J., Mach, T., Heimrath, R., Schardinger, I., Langhammer, F., Biberacher, M., Mair am Tinkhof, O., Strasser, H., Mauthner, F. & Leusbrock, I., Mar 2021, 2021 ed. Wien: Bundesministerium für Klimaschutz, Umwelt, Energie, Mobilität, Innovation und Technologie (BMK) . 141 p. (Berichte aus Energie- und Umweltforschung)
Research output: Book/Report › Commissioned report › peer-review

Open Access
File

Cite this

Stanzel, L., Scholz, J., & Mauthner, F. (2019). A Spatial Data Analysis Approach for Public Policy Simulation in Thermal Energy Transition Scenarios. In P. Haber, T. Lampoltshammer, & M. Mayr (Eds.), Data Science - Analytics and Applications: Proceedings of the 2nd International Data Science Conference – iDSC2019 (pp. 63-68). Springer Vieweg. https://doi.org/10.1007/978-3-658-27495-5_8

A Spatial Data Analysis Approach for Public Policy Simulation in Thermal Energy Transition Scenarios. / Stanzel, Lina; Scholz, Johannes; Mauthner, Franz.
Data Science - Analytics and Applications: Proceedings of the 2nd International Data Science Conference – iDSC2019. ed. / Peter Haber; Thomas Lampoltshammer; Manfred Mayr. Wiesbaden: Springer Vieweg, 2019. p. 63-68.

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Stanzel, L, Scholz, J & Mauthner, F 2019, A Spatial Data Analysis Approach for Public Policy Simulation in Thermal Energy Transition Scenarios. in P Haber, T Lampoltshammer & M Mayr (eds), Data Science - Analytics and Applications: Proceedings of the 2nd International Data Science Conference – iDSC2019. Springer Vieweg, Wiesbaden, pp. 63-68, 2nd International Data Science Conference , Salzburg, Austria, 22/05/19. https://doi.org/10.1007/978-3-658-27495-5_8

Stanzel L, Scholz J, Mauthner F. A Spatial Data Analysis Approach for Public Policy Simulation in Thermal Energy Transition Scenarios. In Haber P, Lampoltshammer T, Mayr M, editors, Data Science - Analytics and Applications: Proceedings of the 2nd International Data Science Conference – iDSC2019. Wiesbaden: Springer Vieweg. 2019. p. 63-68 doi: 10.1007/978-3-658-27495-5_8

Stanzel, Lina ; Scholz, Johannes ; Mauthner, Franz. / A Spatial Data Analysis Approach for Public Policy Simulation in Thermal Energy Transition Scenarios. Data Science - Analytics and Applications: Proceedings of the 2nd International Data Science Conference – iDSC2019. editor / Peter Haber ; Thomas Lampoltshammer ; Manfred Mayr. Wiesbaden : Springer Vieweg, 2019. pp. 63-68

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abstract = "The paper elaborates on an approach to simulate the effect of public policies regarding thermal energy transition pathways in urban communities. The paper discusses the underlying methodologies of calculating Heating Energy demand of buildings and the rationale for potential zones for thermal energy systems. In order to simulate the effects of public policies on communities the authors developed a spatial Agentbased Model, where the buildings are the main objects that are subject to change, based on a number of both technically and socio-demographic parameters. In order to fill a spatial Agentbased Model with data a number of open source and commercially available datasets need to be spatially analyzed and merged. The initial results of the spatial Agent-based Model simulation show that public policies for thermal energy transition can be simulated accordingly.",

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N2 - The paper elaborates on an approach to simulate the effect of public policies regarding thermal energy transition pathways in urban communities. The paper discusses the underlying methodologies of calculating Heating Energy demand of buildings and the rationale for potential zones for thermal energy systems. In order to simulate the effects of public policies on communities the authors developed a spatial Agentbased Model, where the buildings are the main objects that are subject to change, based on a number of both technically and socio-demographic parameters. In order to fill a spatial Agentbased Model with data a number of open source and commercially available datasets need to be spatially analyzed and merged. The initial results of the spatial Agent-based Model simulation show that public policies for thermal energy transition can be simulated accordingly.

AB - The paper elaborates on an approach to simulate the effect of public policies regarding thermal energy transition pathways in urban communities. The paper discusses the underlying methodologies of calculating Heating Energy demand of buildings and the rationale for potential zones for thermal energy systems. In order to simulate the effects of public policies on communities the authors developed a spatial Agentbased Model, where the buildings are the main objects that are subject to change, based on a number of both technically and socio-demographic parameters. In order to fill a spatial Agentbased Model with data a number of open source and commercially available datasets need to be spatially analyzed and merged. The initial results of the spatial Agent-based Model simulation show that public policies for thermal energy transition can be simulated accordingly.

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DO - 10.1007/978-3-658-27495-5_8

M3 - Conference paper

SN - 978-3-658-27494-8

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BT - Data Science - Analytics and Applications

A2 - Haber, Peter

A2 - Lampoltshammer, Thomas

A2 - Mayr, Manfred

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T2 - 2nd International Data Science Conference

Y2 - 22 May 2019 through 24 May 2019

ER -

A Spatial Data Analysis Approach for Public Policy Simulation in Thermal Energy Transition Scenarios

Abstract

Conference

UN SDGs

Access to Document

Fingerprint

Research output

ECC - EnergyCityConcepts: Methoden- und Konzeptentwicklung zur Implementierung nachhaltiger Energiesysteme in Städten am Beispiel von Gleisdorf und Salzburg

Cite this