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A Comparative Study Between Synchrophasor-Measurement-Based Linear and Nonlinear State Estimation in Power Systems

Author

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  • Ali Aljazaeri

    (Faculty of Electrical Engineering and Communication, Brno University of Technology, 60200 Brno, Czech Republic)

  • Petr Toman

    (Faculty of Electrical Engineering and Communication, Brno University of Technology, 60200 Brno, Czech Republic)

  • Obed Muhayimana

    (Faculty of Electrical Engineering and Communication, Brno University of Technology, 60200 Brno, Czech Republic)

Abstract

The evolution of phasor measurement units (PMUs) marked a significant development in the field of electrical engineering. The integration of PMU-based linear state estimators or the augmentation of SCADA measurements with PMU measurements has emerged as a promising solution to address the limitations of conventional state estimation. The utilization of PMU measurements has been demonstrated to effectively address measurement errors, leading to the precise determination of the system’s state within a single iteration. This article provides a comprehensive discussion of both linear and nonlinear state estimation computational processes. A comparative analysis is conducted to assess their performance. PMU-based state estimator models are proposed based on different PMU locations and are further examined under abnormal conditions. The results are compared with the simulated results from a Simulink PSCAD model of the IEEE 14-bus system to ensure validation. The test results demonstrated that the proposed models outperformed the conventional model in terms of robustness and accuracy. The estimated and simulated states matched during both normal and abnormal conditions, demonstrating the model’s capability to track sudden changes in voltage profiles. This article promotes further investigations to develop new control and protection functions using this model.

Suggested Citation

  • Ali Aljazaeri & Petr Toman & Obed Muhayimana, 2025. "A Comparative Study Between Synchrophasor-Measurement-Based Linear and Nonlinear State Estimation in Power Systems," Energies, MDPI, vol. 18(4), pages 1-24, February.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:4:p:983-:d:1593916
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    References listed on IDEAS

    as
    1. Leila Kamyabi & Tek Tjing Lie & Samaneh Madanian & Sarah Marshall, 2024. "A Comprehensive Review of Hybrid State Estimation in Power Systems: Challenges, Opportunities and Prospects," Energies, MDPI, vol. 17(19), pages 1-20, September.
    2. Henrry Moyano & Luis Vargas, 2024. "The Efficiency of the Kalman Filter in Nodal Redundancy," Energies, MDPI, vol. 17(9), pages 1-20, April.
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