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The Application of Hierarchical Clustering to Power Quality Measurements in an Electrical Power Network with Distributed Generation

Author

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  • Michał Jasiński

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

  • Tomasz Sikorski

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

  • Zbigniew Leonowicz

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

  • Klaudiusz Borkowski

    (KGHM Polska Miedź S.A., 50-301 Lubin, Poland)

  • Elżbieta Jasińska

    (Faculty of Law, Administration and Economics, University of Wroclaw, 50-145 Wroclaw, Poland)

Abstract

This article presents the application of data mining (DM) to long-term power quality (PQ) measurements. The Ward algorithm was selected as the cluster analysis (CA) technique to achieve an automatic division of the PQ measurement data. The measurements were conducted in an electrical power network (EPN) of the mining industry with distributed generation (DG). The obtained results indicate that the application of the Ward algorithm to PQ data assures the division with regards to the work of the distributed generation, and also to other important working conditions (e.g., reconfiguration or high harmonic pollution). The presented analysis is conducted for the area-related approach—all measurement point data are connected at an initial stage. The importance rate was proposed in order to indicate the parameters that have a high impact on the classification of the data. Another element of the article was the reduction of the size of the input database. The reduction of input data by 57% assured the classification with a 95% agreement when compared to the complete database classification.

Suggested Citation

  • Michał Jasiński & Tomasz Sikorski & Zbigniew Leonowicz & Klaudiusz Borkowski & Elżbieta Jasińska, 2020. "The Application of Hierarchical Clustering to Power Quality Measurements in an Electrical Power Network with Distributed Generation," Energies, MDPI, vol. 13(9), pages 1-19, May.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:9:p:2407-:d:356755
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    References listed on IDEAS

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    1. Michał Jasiński & Tomasz Sikorski & Paweł Kostyła & Dominika Kaczorowska & Zbigniew Leonowicz & Jacek Rezmer & Jarosław Szymańda & Przemysław Janik & Daniel Bejmert & Marek Rybiański & Elżbieta Jasińs, 2019. "Influence of Measurement Aggregation Algorithms on Power Quality Assessment and Correlation Analysis in Electrical Power Network with PV Power Plant," Energies, MDPI, vol. 12(18), pages 1-18, September.
    2. Chicco, Gianfranco, 2012. "Overview and performance assessment of the clustering methods for electrical load pattern grouping," Energy, Elsevier, vol. 42(1), pages 68-80.
    3. Mengting Yao & Yun Zhu & Junjie Li & Hua Wei & Penghui He, 2019. "Research on Predicting Line Loss Rate in Low Voltage Distribution Network Based on Gradient Boosting Decision Tree," Energies, MDPI, vol. 12(13), pages 1-14, June.
    4. Michał Jasiński & Tomasz Sikorski & Paweł Kostyła & Zbigniew Leonowicz & Klaudiusz Borkowski, 2020. "Combined Cluster Analysis and Global Power Quality Indices for the Qualitative Assessment of the Time-Varying Condition of Power Quality in an Electrical Power Network with Distributed Generation," Energies, MDPI, vol. 13(8), pages 1-21, April.
    5. David L. Olson & Dursun Delen, 2008. "Advanced Data Mining Techniques," Springer Books, Springer, number 978-3-540-76917-0, December.
    6. Lefeng Cheng & Tao Yu, 2018. "Dissolved Gas Analysis Principle-Based Intelligent Approaches to Fault Diagnosis and Decision Making for Large Oil-Immersed Power Transformers: A Survey," Energies, MDPI, vol. 11(4), pages 1-69, April.
    7. Shengli Du & Mingchao Li & Shuai Han & Jonathan Shi & Heng Li, 2019. "Multi-Pattern Data Mining and Recognition of Primary Electric Appliances from Single Non-Intrusive Load Monitoring Data," Energies, MDPI, vol. 12(6), pages 1-20, March.
    8. Razavi, Rouzbeh & Gharipour, Amin & Fleury, Martin & Akpan, Ikpe Justice, 2019. "A practical feature-engineering framework for electricity theft detection in smart grids," Applied Energy, Elsevier, vol. 238(C), pages 481-494.
    9. Ahmad, Tanveer & Chen, Huanxin & Wang, Jiangyu & Guo, Yabin, 2018. "Review of various modeling techniques for the detection of electricity theft in smart grid environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2916-2933.
    10. Ionica Oncioiu & Sorinel Căpuşneanu & Mirela Cătălina Türkeș & Dan Ioan Topor & Dana-Maria Oprea Constantin & Andreea Marin-Pantelescu & Mihaela Ștefan Hint, 2018. "The Sustainability of Romanian SMEs and Their Involvement in the Circular Economy," Sustainability, MDPI, vol. 10(8), pages 1-19, August.
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    Citations

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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. Michal Jasiński & Tomasz Sikorski & Dominika Kaczorowska & Jacek Rezmer & Vishnu Suresh & Zbigniew Leonowicz & Paweł Kostyla & Jarosław Szymańda & Przemysław Janik, 2020. "A Case Study on Power Quality in a Virtual Power Plant: Long Term Assessment and Global Index Application," Energies, MDPI, vol. 13(24), pages 1-20, December.
    3. 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.
    4. Zbigniew Leonowicz & Michał Jasiński, 2021. "Signal Analysis in Power Systems," Energies, MDPI, vol. 14(23), pages 1-3, November.

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