IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i8p2050-d347908.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/8/2050/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/8/2050/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. Zbigniew Leonowicz & Michał Jasiński, 2021. "Signal Analysis in Power Systems," Energies, MDPI, vol. 14(23), pages 1-3, November.
    3. Julio Barros, 2022. "New Power Quality Measurement Techniques and Indices in DC and AC Networks," Energies, MDPI, vol. 15(23), pages 1-3, December.
    4. 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.
    5. 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).
    6. 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.
    7. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Haidar, Ahmed M.A. & Muttaqi, Kashem & Sutanto, Danny, 2015. "Smart Grid and its future perspectives in Australia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1375-1389.
    2. Li, Yang & Wang, Jinlong & Zhao, Dongbo & Li, Guoqing & Chen, Chen, 2018. "A two-stage approach for combined heat and power economic emission dispatch: Combining multi-objective optimization with integrated decision making," Energy, Elsevier, vol. 162(C), pages 237-254.
    3. Capozzoli, Alfonso & Piscitelli, Marco Savino & Brandi, Silvio & Grassi, Daniele & Chicco, Gianfranco, 2018. "Automated load pattern learning and anomaly detection for enhancing energy management in smart buildings," Energy, Elsevier, vol. 157(C), pages 336-352.
    4. Shen, Boyang & Chen, Yu & Li, Chuanyue & Wang, Sheng & Chen, Xiaoyuan, 2021. "Superconducting fault current limiter (SFCL): Experiment and the simulation from finite-element method (FEM) to power/energy system software," Energy, Elsevier, vol. 234(C).
    5. Molina-Solana, Miguel & Ros, María & Ruiz, M. Dolores & Gómez-Romero, Juan & Martin-Bautista, M.J., 2017. "Data science for building energy management: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 598-609.
    6. Zhou, Kaile & Yang, Shanlin, 2015. "A framework of service-oriented operation model of China׳s power system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 719-725.
    7. Tomasz Sikorski & Michal Jasiński & Edyta Ropuszyńska-Surma & Magdalena Węglarz & Dominika Kaczorowska & Paweł Kostyla & Zbigniew Leonowicz & Robert Lis & Jacek Rezmer & Wilhelm Rojewski & Marian Sobi, 2020. "A Case Study on Distributed Energy Resources and Energy-Storage Systems in a Virtual Power Plant Concept: Technical Aspects," Energies, MDPI, vol. 13(12), pages 1-30, June.
    8. Igual, R. & Medrano, C., 2020. "Research challenges in real-time classification of power quality disturbances applicable to microgrids: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    9. 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).
    10. Hyun Cheol Jeong & Jaesung Jung & Byung O Kang, 2020. "Development of Operational Strategies of Energy Storage System Using Classification of Customer Load Profiles under Time-of-Use Tariffs in South Korea," Energies, MDPI, vol. 13(7), pages 1-17, April.
    11. 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.
    12. Irfan, Muhammad & Iqbal, Jamshed & Iqbal, Adeel & Iqbal, Zahid & Riaz, Raja Ali & Mehmood, Adeel, 2017. "Opportunities and challenges in control of smart grids – Pakistani perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 652-674.
    13. Bielecki, Sławomir & Skoczkowski, Tadeusz, 2018. "An enhanced concept of Q-power management," Energy, Elsevier, vol. 162(C), pages 335-353.
    14. Fei Mei & Yong Ren & Qingliang Wu & Chenyu Zhang & Yi Pan & Haoyuan Sha & Jianyong Zheng, 2018. "Online Recognition Method for Voltage Sags Based on a Deep Belief Network," Energies, MDPI, vol. 12(1), pages 1-16, December.
    15. Zhou, Kaile & Yang, Shanlin, 2016. "Emission reduction of China׳s steel industry: Progress and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 319-327.
    16. Yang, Shuxia & Wang, Xiongfei & Xu, Jiayu & Tang, Mingrun & Chen, Guang, 2023. "Distribution network adaptability assessment considering distributed PV “reverse power flow” behavior - a case study in Beijing," Energy, Elsevier, vol. 275(C).
    17. Ventosa-Cutillas, Antonio & Montero-Robina, Pablo & Cuesta, Federico & Gordillo, Francisco, 2020. "A simple modulation approach for interfacing three-level Neutral-Point-Clamped converters to the grid," Energy, Elsevier, vol. 205(C).
    18. Reddy, K.S. & Kumar, Madhusudan & Mallick, T.K. & Sharon, H. & Lokeswaran, S., 2014. "A review of Integration, Control, Communication and Metering (ICCM) of renewable energy based smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 180-192.
    19. Krzysztof Chmielowiec & Łukasz Topolski & Aleks Piszczek & Tomasz Rodziewicz & Zbigniew Hanzelka, 2022. "Study on Energy Efficiency and Harmonic Emission of Photovoltaic Inverters," Energies, MDPI, vol. 15(8), pages 1-23, April.
    20. Li, Han & Wang, Zhe & Hong, Tianzhen & Parker, Andrew & Neukomm, Monica, 2021. "Characterizing patterns and variability of building electric load profiles in time and frequency domains," Applied Energy, Elsevier, vol. 291(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:13:y:2020:i:8:p:2050-:d:347908. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.