Novel method to simulate large-scale thermal city models

Publikation: Beitrag in Fachzeitschrift/ZeitungArtikel

Abstract

This study presents a method used to simulate large-scale thermal models of cities that achieves two improvements compared to the state-of-the-art techniques: 1) Current state-of-the-art methods cannot simulate the dynamic interaction between subcomponents of a smart energy system at urban scale. This method proposes detailed dynamic simulation approaches for large-scale thermal models. 2) Currently applied co-simulation frameworks are not applicable to large-scale models. In the present study, the dynamic building simulation tool IDA Indoor Climate and Energy, which uses parallelization methods for large-scale models, is coupled with a co-simulation platform. The methods are applied to a semi-virtual case study, which consists of 1561 buildings and a new development area. The building stock is analyzed
using an automated method based on publicly available data. In contrast, the virtual urban development area is investigated using a co-simulation framework with three dynamic simulation tools: IDA Indoor Climate and Energy for buildings (256 thermal zones and 29 heating systems), TRNSYS for the energy
supply unit and Dymola/Modelica for the district heating network. The in fluence of co-simulation on the accuracy and on the computation time are investigated. The major finding of this study is that the computation time can be significantly reduced by decoupling methods.
Spracheenglisch
Seiten633 - 646
Seitenumfang14
ZeitschriftEnergy
Band157
DOIs
StatusVeröffentlicht - 15 Aug 2018

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    Novel method to simulate large-scale thermal city models. / Nageler, Peter Josef; Schweiger, Gerald; Schranzhofer, Hermann; Mach, Thomas; Heimrath, Richard; Hochenauer, Christoph.

    in: Energy, Band 157, 15.08.2018, S. 633 - 646.

    Publikation: Beitrag in Fachzeitschrift/ZeitungArtikel

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    title = "Novel method to simulate large-scale thermal city models",
    abstract = "This study presents a method used to simulate large-scale thermal models of cities that achieves two improvements compared to the state-of-the-art techniques: 1) Current state-of-the-art methods cannot simulate the dynamic interaction between subcomponents of a smart energy system at urban scale. This method proposes detailed dynamic simulation approaches for large-scale thermal models. 2) Currently applied co-simulation frameworks are not applicable to large-scale models. In the present study, the dynamic building simulation tool IDA Indoor Climate and Energy, which uses parallelization methods for large-scale models, is coupled with a co-simulation platform. The methods are applied to a semi-virtual case study, which consists of 1561 buildings and a new development area. The building stock is analyzedusing an automated method based on publicly available data. In contrast, the virtual urban development area is investigated using a co-simulation framework with three dynamic simulation tools: IDA Indoor Climate and Energy for buildings (256 thermal zones and 29 heating systems), TRNSYS for the energysupply unit and Dymola/Modelica for the district heating network. The in fluence of co-simulation on the accuracy and on the computation time are investigated. The major finding of this study is that the computation time can be significantly reduced by decoupling methods.",
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    AU - Nageler,Peter Josef

    AU - Schweiger,Gerald

    AU - Schranzhofer,Hermann

    AU - Mach,Thomas

    AU - Heimrath,Richard

    AU - Hochenauer,Christoph

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    N2 - This study presents a method used to simulate large-scale thermal models of cities that achieves two improvements compared to the state-of-the-art techniques: 1) Current state-of-the-art methods cannot simulate the dynamic interaction between subcomponents of a smart energy system at urban scale. This method proposes detailed dynamic simulation approaches for large-scale thermal models. 2) Currently applied co-simulation frameworks are not applicable to large-scale models. In the present study, the dynamic building simulation tool IDA Indoor Climate and Energy, which uses parallelization methods for large-scale models, is coupled with a co-simulation platform. The methods are applied to a semi-virtual case study, which consists of 1561 buildings and a new development area. The building stock is analyzedusing an automated method based on publicly available data. In contrast, the virtual urban development area is investigated using a co-simulation framework with three dynamic simulation tools: IDA Indoor Climate and Energy for buildings (256 thermal zones and 29 heating systems), TRNSYS for the energysupply unit and Dymola/Modelica for the district heating network. The in fluence of co-simulation on the accuracy and on the computation time are investigated. The major finding of this study is that the computation time can be significantly reduced by decoupling methods.

    AB - This study presents a method used to simulate large-scale thermal models of cities that achieves two improvements compared to the state-of-the-art techniques: 1) Current state-of-the-art methods cannot simulate the dynamic interaction between subcomponents of a smart energy system at urban scale. This method proposes detailed dynamic simulation approaches for large-scale thermal models. 2) Currently applied co-simulation frameworks are not applicable to large-scale models. In the present study, the dynamic building simulation tool IDA Indoor Climate and Energy, which uses parallelization methods for large-scale models, is coupled with a co-simulation platform. The methods are applied to a semi-virtual case study, which consists of 1561 buildings and a new development area. The building stock is analyzedusing an automated method based on publicly available data. In contrast, the virtual urban development area is investigated using a co-simulation framework with three dynamic simulation tools: IDA Indoor Climate and Energy for buildings (256 thermal zones and 29 heating systems), TRNSYS for the energysupply unit and Dymola/Modelica for the district heating network. The in fluence of co-simulation on the accuracy and on the computation time are investigated. The major finding of this study is that the computation time can be significantly reduced by decoupling methods.

    KW - Dynamic urban energy simulation

    KW - Co-simulation IDA ICE/BCVTB

    KW - Model decoupling

    KW - Parallelization

    KW - Variable simulation timestep

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