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A Case Study on a Hierarchical Clustering Application in a Virtual Power Plant: Detection of Specific Working Conditions from Power Quality Data

Author

Listed:
  • Michał Jasiński

    (Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland)

  • Tomasz Sikorski

    (Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland)

  • Dominika Kaczorowska

    (Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland)

  • Jacek Rezmer

    (Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland)

  • Vishnu Suresh

    (Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland)

  • Zbigniew Leonowicz

    (Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland)

  • Paweł Kostyła

    (Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland)

  • Jarosław Szymańda

    (Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland)

  • Przemysław Janik

    (TAURON Ekoenergia Ltd., 58-500 Jelenia Góra, Poland)

  • Jacek Bieńkowski

    (TAURON Ekoenergia Ltd., 58-500 Jelenia Góra, Poland)

  • Przemysław Prus

    (TAURON Ekoenergia Ltd., 58-500 Jelenia Góra, Poland)

Abstract

The integration of virtual power plants (VPP) has become more popular. Thus, research on VPP for different issues is highly desirable. This article addresses power quality issues. The presented investigation is based on multipoint, synchronic measurements obtained from five points that are related to the VPP. This article provides a proposition and discussion of using one global index in place of the classical power quality (PQ) parameters. Furthermore, in the article, one new global power quality index was proposed. Then the PQ measurements, as well as global indexes, were used to prepare input databases for cluster analysis. The mentioned cluster analysis aimed to detect the short-term working conditions of VPP that were specific from the point of view of power quality. To realize this the hierarchical clustering using the Ward algorithm was realized. The article also presents the application of the cubic clustering criterion to support cluster analysis. Then the assessment of the obtained condition was realized using the global index to assure the general information of the cause of its occurrence. Furthermore, the article noticed that the application of the global index, assured reduction of database size to around 74%, without losing the features of the data.

Suggested Citation

  • Michał Jasiński & Tomasz Sikorski & Dominika Kaczorowska & Jacek Rezmer & Vishnu Suresh & Zbigniew Leonowicz & Paweł Kostyła & Jarosław Szymańda & Przemysław Janik & Jacek Bieńkowski & Przemysław Prus, 2021. "A Case Study on a Hierarchical Clustering Application in a Virtual Power Plant: Detection of Specific Working Conditions from Power Quality Data," Energies, MDPI, vol. 14(4), pages 1-13, February.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:4:p:907-:d:496498
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    References listed on IDEAS

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    Cited by:

    1. Fachrizal Aksan & Michał Jasiński & Tomasz Sikorski & Dominika Kaczorowska & Jacek Rezmer & Vishnu Suresh & Zbigniew Leonowicz & Paweł Kostyła & Jarosław Szymańda & Przemysław Janik, 2021. "Clustering Methods for Power Quality Measurements in Virtual Power Plant," Energies, MDPI, vol. 14(18), pages 1-20, September.
    2. Zbigniew Leonowicz & Michal Jasinski, 2022. "Machine Learning and Data Mining Applications in Power Systems," Energies, MDPI, vol. 15(5), pages 1-2, February.

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