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A Template-Based Approach for Generating Modelica Models of Building Electrical Systems from Semantic Models.

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Title: A Template-Based Approach for Generating Modelica Models of Building Electrical Systems from Semantic Models.
Authors: Waghale, Anay1 (AUTHOR) anay.waghale@pnnl.gov, Devaprasad, Karthikeya1 (AUTHOR), Gupta, Trisha1 (AUTHOR), Poplawski, Michael1 (AUTHOR)
Source: Energies (19961073). Jun2026, Vol. 19 Issue 11, p2586. 28p.
Subject Terms: *Hybrid power systems, *Modeling languages (Computer science), *Workflow, *Automation, *Conceptual models, *Python programming language, *Electric networks, *Electrical load
Abstract: Building electrical systems are becoming increasingly complex as designers evaluate AC, DC, and hybrid distribution architectures, integrate distributed energy resources, and maintain alignment with evolving performance and reliability goals. Existing design tools are typically limited, non-interoperable, and unable to support continuous modeling across design phases, resulting in fragmented workflows and significant manual effort. This paper presents a template-based workflow that automates the generation of high-fidelity Modelica simulation models of building electrical systems from semantic models. The workflow supports both basic safety analysis and the power-flow simulation of AC, DC, and hybrid system architectures. A Python-based middleware (RDF2EMO) was developed to automate data extraction, template instantiation, and parametric model generation, enabling rapid and consistent iteration through schematic design, design development, and construction documentation phases. Verification of the middleware automation (RDF2EMO) using a reference medium-sized office building demonstrates that the generated Modelica model is internally consistent with the Building Information Model. A case study demonstrates how the workflow supports design decisions, including system architecture selection, equipment sizing impacts and optimization, and reliability analysis. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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  Availability: 1
Header DbId: enr
DbLabel: Energy & Power Source
An: 194587974
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: A Template-Based Approach for Generating Modelica Models of Building Electrical Systems from Semantic Models.
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  Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. Jun2026, Vol. 19 Issue 11, p2586. 28p.
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  Data: *<searchLink fieldCode="DE" term="%22Hybrid+power+systems%22">Hybrid power systems</searchLink><br />*<searchLink fieldCode="DE" term="%22Modeling+languages+%28Computer+science%29%22">Modeling languages (Computer science)</searchLink><br />*<searchLink fieldCode="DE" term="%22Workflow%22">Workflow</searchLink><br />*<searchLink fieldCode="DE" term="%22Automation%22">Automation</searchLink><br />*<searchLink fieldCode="DE" term="%22Conceptual+models%22">Conceptual models</searchLink><br />*<searchLink fieldCode="DE" term="%22Python+programming+language%22">Python programming language</searchLink><br />*<searchLink fieldCode="DE" term="%22Electric+networks%22">Electric networks</searchLink><br />*<searchLink fieldCode="DE" term="%22Electrical+load%22">Electrical load</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: Building electrical systems are becoming increasingly complex as designers evaluate AC, DC, and hybrid distribution architectures, integrate distributed energy resources, and maintain alignment with evolving performance and reliability goals. Existing design tools are typically limited, non-interoperable, and unable to support continuous modeling across design phases, resulting in fragmented workflows and significant manual effort. This paper presents a template-based workflow that automates the generation of high-fidelity Modelica simulation models of building electrical systems from semantic models. The workflow supports both basic safety analysis and the power-flow simulation of AC, DC, and hybrid system architectures. A Python-based middleware (RDF2EMO) was developed to automate data extraction, template instantiation, and parametric model generation, enabling rapid and consistent iteration through schematic design, design development, and construction documentation phases. Verification of the middleware automation (RDF2EMO) using a reference medium-sized office building demonstrates that the generated Modelica model is internally consistent with the Building Information Model. A case study demonstrates how the workflow supports design decisions, including system architecture selection, equipment sizing impacts and optimization, and reliability analysis. [ABSTRACT FROM AUTHOR]
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=194587974
RecordInfo BibRecord:
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        Value: 10.3390/en19112586
    Languages:
      – Code: eng
        Text: English
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        PageCount: 28
        StartPage: 2586
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      – SubjectFull: Hybrid power systems
        Type: general
      – SubjectFull: Modeling languages (Computer science)
        Type: general
      – SubjectFull: Workflow
        Type: general
      – SubjectFull: Automation
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      – SubjectFull: Conceptual models
        Type: general
      – SubjectFull: Python programming language
        Type: general
      – SubjectFull: Electric networks
        Type: general
      – SubjectFull: Electrical load
        Type: general
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      – TitleFull: A Template-Based Approach for Generating Modelica Models of Building Electrical Systems from Semantic Models.
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            NameFull: Devaprasad, Karthikeya
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            NameFull: Gupta, Trisha
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            NameFull: Poplawski, Michael
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            – D: 01
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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