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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

Author

Listed:
  • 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)

  • Paweł Kostyła

    (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, 59-301 Lubin, Poland)

Abstract

This paper presents the idea of a combined analysis of long-term power quality data using cluster analysis (CA) and global power quality indices (GPQIs). The aim of the proposed method is to obtain a solution for the automatic identification and assessment of different power quality condition levels that may be caused by different working conditions of an observed electrical power network (EPN). CA is used for identifying the period when the power quality data represents a different level. GPQIs are proposed to calculate a simplified assessment of the power quality condition of the data collected using CA. Two proposed global power quality indices have been introduced for this purpose, one for 10-min aggregated data and the other for events—the aggregated data index ( ADI ) and the flagged data index ( FDI ), respectively. In order to investigate the advantages and disadvantages of the proposed method, several investigations were performed, using real measurements in an electrical power network with distributed generation (DG) supplying the copper mining industry. The investigations assessed the proposed method, examining whether it could identify the impact of DG and other network working conditions on power quality level conditions. The obtained results indicate that the proposed method is a suitable tool for quick comparison between data collected in the identified clusters. Additionally, the proposed method is implemented for the data collected from many measurement points belonging to the observed area of an EPN in a simultaneous and synchronous way. Thus, the proposed method can also be considered for power quality assessment and is an alternative approach to the classic multiparameter analysis of power quality data addressed to particular measurement points.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:8:p:2050-:d:347908
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    References listed on IDEAS

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    1. Elbasuony, Ghada S. & Abdel Aleem, Shady H.E. & Ibrahim, Ahmed M. & Sharaf, Adel M., 2018. "A unified index for power quality evaluation in distributed generation systems," Energy, Elsevier, vol. 149(C), pages 607-622.
    2. 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.
    3. Van Ky Huynh & Van Duong Ngo & Dinh Duong Le & Nhi Thi Ai Nguyen, 2018. "Probabilistic Power Flow Methodology for Large-Scale Power Systems Incorporating Renewable Energy Sources," Energies, MDPI, vol. 11(10), pages 1-12, October.
    4. Mahela, Om Prakash & Shaik, Abdul Gafoor, 2017. "Power quality recognition in distribution system with solar energy penetration using S-transform and Fuzzy C-means clustering," Renewable Energy, Elsevier, vol. 106(C), pages 37-51.
    5. Zhou, Kai-le & Yang, Shan-lin & Shen, Chao, 2013. "A review of electric load classification in smart grid environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 103-110.
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    Citations

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    Cited by:

    1. Paweł Sokólski & Tomasz A. Rutkowski & Bartosz Ceran & Daria Złotecka & Dariusz Horla, 2022. "Numbers, Please: Power- and Voltage-Related Indices in Control of a Turbine-Generator Set," Energies, MDPI, vol. 15(7), pages 1-24, March.
    2. Julio Barros, 2022. "New Power Quality Measurement Techniques and Indices in DC and AC Networks," Energies, MDPI, vol. 15(23), pages 1-3, 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 Data Mining Application in a Virtual Power Plant: Cluster Analysis of Power Quality Measurements," Energies, MDPI, vol. 14(4), pages 1-14, February.
    4. Gerber, Daniel L. & Ghatpande, Omkar A. & Nazir, Moazzam & Heredia, Willy G. Bernal & Feng, Wei & Brown, Richard E., 2022. "Energy and power quality measurement for electrical distribution in AC and DC microgrid buildings," Applied Energy, Elsevier, vol. 308(C).
    5. 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.
    6. 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.
    7. Zbigniew Leonowicz & Michał Jasiński, 2021. "Signal Analysis in Power Systems," Energies, MDPI, vol. 14(23), pages 1-3, November.

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