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Comprehensive Power Quality Assessment Based on a Data-Driven Determinant-Valued Extension Hierarchical Analysis Approach

Author

Listed:
  • Jingyi Zhang

    (State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209, China)

  • Tongtian Sheng

    (State Grid Corporation of China, Beijing 100031, China)

  • Pan Gu

    (State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209, China)

  • Miao Yu

    (School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
    Beijing Engineering Research Center for Building Safety Inspection, Beijing 100044, China)

  • Honghao Wu

    (School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
    Beijing Engineering Research Center for Building Safety Inspection, Beijing 100044, China)

  • Jianqun Sun

    (School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
    Beijing Engineering Research Center for Building Safety Inspection, Beijing 100044, China)

  • Jinming Bao

    (State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209, China)

Abstract

The increasing demand for power quality in modern power supply facilities and the deepening changes in the power market have led to frequent power quality events, making the assessment of power quality a necessity. In view of the complexity of the model and the sensitivity of the parameters of the existing power quality assessment system, as well as the shortcomings of the traditional hierarchical analysis method, this paper proposes a data-driven power quality assessment system based on the improved determinant-valued extension hierarchical analysis, which makes the factors affecting power quality hierarchical, and enhances the conservatism of the matrix while reducing the human subjective factors, so as to analyze the main power quality problems in a clearer and more intuitive way. The evaluation system is validated and analyzed, and the corresponding evaluation result is “excellent”, which proves that the system effectively evaluates the power quality in real scenarios, and has a good prospect in power quality evaluation.

Suggested Citation

  • Jingyi Zhang & Tongtian Sheng & Pan Gu & Miao Yu & Honghao Wu & Jianqun Sun & Jinming Bao, 2024. "Comprehensive Power Quality Assessment Based on a Data-Driven Determinant-Valued Extension Hierarchical Analysis Approach," Energies, MDPI, vol. 17(13), pages 1-14, June.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:13:p:3141-:d:1422185
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    References listed on IDEAS

    as
    1. Ning Wang & Shuai Zheng & Weiqiang Gao, 2022. "Microgrid Harmonic Mitigation Strategy Based on the Optimal Allocation of Active Power and Harmonic Mitigation Capacities of Multi-Functional Grid-Connected Inverters," Energies, MDPI, vol. 15(17), pages 1-20, August.
    2. Nuno M. Rodrigues & Fernando M. Janeiro & Pedro M. Ramos, 2023. "Power Quality Transient Detection and Characterization Using Deep Learning Techniques," Energies, MDPI, vol. 16(4), pages 1-11, February.
    Full references (including those not matched with items on IDEAS)

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