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A Case Study on Data Mining Application in a Virtual Power Plant: Cluster Analysis of Power Quality Measurements

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
    Faculty of Mechanical and Power Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland)

  • Przemysław Prus

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

Abstract

One of the recent trends that concern renewable energy sources and energy storage systems is the concept of virtual power plants (VPP). The majority of research now focuses on analyzing case studies of VPP in different issues. This article presents the investigation that is based on a real VPP. That VPP operates in Poland and consists of hydropower plants (HPP), as well as energy storage systems (ESS). For specific analysis, cluster analysis, as a representative technique of data mining, was selected for power quality (PQ) issues. The used data represents 26 weeks of PQ multipoint synchronic measurements for 5 related to VPP points. The investigation discusses different input databases for cluster analysis. Moreover, as an extension to using classical PQ parameters as an input, the application of the global index was proposed. This enables the reduction of the size of the input database with maintaining the data features for cluster analysis. Moreover, the problem of the optimal number of cluster selection is discussed. Finally, the assessment of clustering results was performed to assess the VPP impact on PQ level.

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 Data Mining Application in a Virtual Power Plant: Cluster Analysis of Power Quality Measurements," Energies, MDPI, vol. 14(4), pages 1-14, February.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:4:p:974-:d:498476
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    References listed on IDEAS

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    Cited by:

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    2. Zbigniew Leonowicz & Michal Jasinski, 2022. "Machine Learning and Data Mining Applications in Power Systems," Energies, MDPI, vol. 15(5), pages 1-2, February.
    3. Anqi Yang & Shudong Yang, 2023. "The Impact of the Implementation of International Law on Marine Environmental Protection on International Public Health Driven by Multi-Source Network Comment Mining," IJERPH, MDPI, vol. 20(6), pages 1-16, March.

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