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Integrated Simulation and Calibration Framework for Heating System Optimization.

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Název: Integrated Simulation and Calibration Framework for Heating System Optimization.
Autoři: Djebko, Kirill, Weidner, Daniel, Waleska, Marcel, Krey, Timo, Rausch, Sven, Seipel, Dietmar, Puppe, Frank
Zdroj: Sensors (14248220); Feb2024, Vol. 24 Issue 3, p886, 28p
Témata: MATHEMATICAL optimization, DIGITAL twin, CALIBRATION, DATA augmentation, MISSING data (Statistics), BOILERS, HEATING
Abstrakt: In a time where sustainability and CO2 efficiency are of ever-increasing importance, heating systems deserve special considerations. Despite well-functioning hardware, inefficiencies may arise when controller parameters are not well chosen. While monitoring systems could help to identify such issues, they lack improvement suggestions. One possible solution would be the use of digital twins; however, critical values such as the water consumption of the residents can often not be acquired for accurate models. To address this issue, coarse models can be employed to generate quantitative predictions, which can then be interpreted qualitatively to assess "better or worse" system behavior. In this paper, we present a simulation and calibration framework as well as a preprocessing module. These components can be run locally or deployed as containerized microservices and are easy to interface with existing data acquisition infrastructure. We evaluate the two main operating modes, namely automatic model calibration, using measured data, and the optimization of controller parameters. Our results show that using a coarse model of a real heating system and data augmentation through preprocessing, it is possible to achieve an acceptable fit of partially incomplete measured data, and that the calibrated model can subsequently be used to perform an optimization of the controller parameters in regard to the simulated boiler gas consumption. [ABSTRACT FROM AUTHOR]
Copyright of Sensors (14248220) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Integrated Simulation and Calibration Framework for Heating System Optimization.
– Name: Author
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  Data: <searchLink fieldCode="AR" term="%22Djebko%2C+Kirill%22">Djebko, Kirill</searchLink><br /><searchLink fieldCode="AR" term="%22Weidner%2C+Daniel%22">Weidner, Daniel</searchLink><br /><searchLink fieldCode="AR" term="%22Waleska%2C+Marcel%22">Waleska, Marcel</searchLink><br /><searchLink fieldCode="AR" term="%22Krey%2C+Timo%22">Krey, Timo</searchLink><br /><searchLink fieldCode="AR" term="%22Rausch%2C+Sven%22">Rausch, Sven</searchLink><br /><searchLink fieldCode="AR" term="%22Seipel%2C+Dietmar%22">Seipel, Dietmar</searchLink><br /><searchLink fieldCode="AR" term="%22Puppe%2C+Frank%22">Puppe, Frank</searchLink>
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  Data: Sensors (14248220); Feb2024, Vol. 24 Issue 3, p886, 28p
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22MATHEMATICAL+optimization%22">MATHEMATICAL optimization</searchLink><br /><searchLink fieldCode="DE" term="%22DIGITAL+twin%22">DIGITAL twin</searchLink><br /><searchLink fieldCode="DE" term="%22CALIBRATION%22">CALIBRATION</searchLink><br /><searchLink fieldCode="DE" term="%22DATA+augmentation%22">DATA augmentation</searchLink><br /><searchLink fieldCode="DE" term="%22MISSING+data+%28Statistics%29%22">MISSING data (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22BOILERS%22">BOILERS</searchLink><br /><searchLink fieldCode="DE" term="%22HEATING%22">HEATING</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: In a time where sustainability and CO2 efficiency are of ever-increasing importance, heating systems deserve special considerations. Despite well-functioning hardware, inefficiencies may arise when controller parameters are not well chosen. While monitoring systems could help to identify such issues, they lack improvement suggestions. One possible solution would be the use of digital twins; however, critical values such as the water consumption of the residents can often not be acquired for accurate models. To address this issue, coarse models can be employed to generate quantitative predictions, which can then be interpreted qualitatively to assess "better or worse" system behavior. In this paper, we present a simulation and calibration framework as well as a preprocessing module. These components can be run locally or deployed as containerized microservices and are easy to interface with existing data acquisition infrastructure. We evaluate the two main operating modes, namely automatic model calibration, using measured data, and the optimization of controller parameters. Our results show that using a coarse model of a real heating system and data augmentation through preprocessing, it is possible to achieve an acceptable fit of partially incomplete measured data, and that the calibrated model can subsequently be used to perform an optimization of the controller parameters in regard to the simulated boiler gas consumption. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Sensors (14248220) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.3390/s24030886
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 28
        StartPage: 886
    Subjects:
      – SubjectFull: MATHEMATICAL optimization
        Type: general
      – SubjectFull: DIGITAL twin
        Type: general
      – SubjectFull: CALIBRATION
        Type: general
      – SubjectFull: DATA augmentation
        Type: general
      – SubjectFull: MISSING data (Statistics)
        Type: general
      – SubjectFull: BOILERS
        Type: general
      – SubjectFull: HEATING
        Type: general
    Titles:
      – TitleFull: Integrated Simulation and Calibration Framework for Heating System Optimization.
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            NameFull: Djebko, Kirill
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            NameFull: Waleska, Marcel
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            NameFull: Seipel, Dietmar
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            – D: 01
              M: 02
              Text: Feb2024
              Type: published
              Y: 2024
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