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Research on CBM of the Intelligent Substation SCADA System

Author

Listed:
  • Jyh-Cherng Gu

    (Department of Electrical Engineering, National Taiwan University of Science and Technology, 43, Sec. 3, Keelung Road, Taipei 10607, Taiwan)

  • Chun-Hung Liu

    (Department of Electrical Engineering, National Taiwan University of Science and Technology, 43, Sec. 3, Keelung Road, Taipei 10607, Taiwan)

  • Kai-Ying Chou

    (Department of Electrical Engineering, National Taiwan University of Science and Technology, 43, Sec. 3, Keelung Road, Taipei 10607, Taiwan)

  • Ming-Ta Yang

    (Department of Electrical Engineering, St. John’s University, 499, Sec. 4, Tam King Road, Tamsui District, New Taipei City 25135, Taiwan)

Abstract

An equipment status management and maintenance platform of an intelligent substation monitoring and control system is built in the Tai-Tam substation of the Taipower company. The real-time operating status of the equipment, such as the server, supervisory control and data acquisition (SCADA) human–machine interface (HMI) software, switches, intelligent electronic devices (IEDs), merging units (MUs), as well as the entire SCADA system, are evaluated comprehensively. First, the status information of all equipment is collected, and the theory of relative deterioration degree (RDD) and fuzzy theory (FT) are applied to calculate the fuzzy evaluation matrix of the equipment influencing factors. Then, the subjective analytic hierarchy process (AHP) and the objective entropy method for weighting are combined to calculate the comprehensive weights of the equipment influencing factors. Finally, the result of the equipment status evaluation is obtained using the fuzzy comprehensive evaluation (FCE) method and is presented at the equipment status management and maintenance platform. Such equipment status evaluation results can be used by the inspection and maintenance personnel to determine the priority for equipment maintenance and repair. The result of this study may serve as a valuable reference to utility companies when making maintenance plans.

Suggested Citation

  • Jyh-Cherng Gu & Chun-Hung Liu & Kai-Ying Chou & Ming-Ta Yang, 2019. "Research on CBM of the Intelligent Substation SCADA System," Energies, MDPI, vol. 12(20), pages 1-22, October.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:20:p:3892-:d:276536
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    References listed on IDEAS

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    1. Masoud Asgarpour & John Dalsgaard Sørensen, 2018. "Bayesian Based Diagnostic Model for Condition Based Maintenance of Offshore Wind Farms," Energies, MDPI, vol. 11(2), pages 1-17, January.
    2. Fenglan Tian & Zhongzhao Jing & Huan Zhao & Enze Zhang & Jiefeng Liu, 2019. "A Synthetic Condition Assessment Model for Power Transformers Using the Fuzzy Evidence Fusion Method," Energies, MDPI, vol. 12(5), pages 1-17, March.
    3. Jannie S. Nielsen & John D. Sørensen, 2017. "Bayesian Estimation of Remaining Useful Life for Wind Turbine Blades," Energies, MDPI, vol. 10(5), pages 1-13, May.
    4. Peng Qian & Xiange Tian & Jamil Kanfoud & Joash Lap Yan Lee & Tat-Hean Gan, 2019. "A Novel Condition Monitoring Method of Wind Turbines Based on Long Short-Term Memory Neural Network," Energies, MDPI, vol. 12(18), pages 1-15, September.
    5. Yi Yang & John Dalsgaard Sørensen, 2019. "Cost-Optimal Maintenance Planning for Defects on Wind Turbine Blades," Energies, MDPI, vol. 12(6), pages 1-16, March.
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    Cited by:

    1. Cristini, Hélène & Kauppinen-Räisänen, Hannele, 2020. "Managing the transformation of the global commons into luxuries for all," Journal of Business Research, Elsevier, vol. 116(C), pages 467-473.

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