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A Robust Asynchrophasor in PMU Using Second-Order Kalman Filter

Nayef Alqahtani1,2,*, Ali Alqahtani3

1 Electrical and Computer Engineering Department, School of Engineering and Computer Science, Oakland University, Rochester, MI, 48326, USA
2 King Faisal University, Al-Ahsa, 31982, Kingdom of Saudi Arabia
3 Department of Networks and Communications Engineering, Najran University, Najran, 61441, Kingdom of Saudi Arabia

* Corresponding Author: Nayef Alqahtani. Email: email

Computers, Materials & Continua 2023, 74(2), 2557-2573.


Phasor Measurement Units (PMUs) provide Global Positioning System (GPS) time-stamped synchronized measurements of voltage and current with the phase angle of the system at certain points along with the grid system. Those synchronized data measurements are extracted in the form of amplitude and phase from various locations of the power grid to monitor and control the power system condition. A PMU device is a crucial part of the power equipment in terms of the cost and operative point of view. However, such ongoing development and improvement to PMUs’ principal work are essential to the network operators to enhance the grid quality and the operating expenses. This paper introduces a proposed method that led to low-cost and less complex techniques to optimize the performance of PMU using Second-Order Kalman Filter. It is based on the Asyncrhophasor technique resulting in a phase error minimization when receiving the signal from an access point or from the main access point. The MATLAB model has been created to implement the proposed method in the presence of Gaussian and non-Gaussian. The results have shown the proposed method which is Second-Order Kalman Filter outperforms the existing model. The results were tested using Mean Square Error (MSE). The proposed Second-Order Kalman Filter method has been replaced with a synchronization unit into the PMU structure to clarify the significance of the proposed new PMU.


Cite This Article

N. Alqahtani and A. Alqahtani, "A robust asynchrophasor in pmu using second-order kalman filter," Computers, Materials & Continua, vol. 74, no.2, pp. 2557–2573, 2023.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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