Robust estimation of frequency and RoCoF in modern power systems
Robust estimation of frequency and RoCoF in modern power systems
The extent in the estimation of frequency and rate of change of frequency (RoCoF) plays an important role in providing power system stability, preventing equipment damage, and thus ensuring reliability of the grid. The inevitable shift from synchronous generators to inverter dependent generation has substantially reduced the overall system inertia which causes rapid frequency variations reflecting in the RoCoF where it fluctuates up to ±1 Hz/s. This range of fluctuations can cause relay malfunctions leading to cascading failures in the system. This chapter discusses two advanced methodologies to address such challenges, namely the interpolated discrete Fourier transform (IpDFT) with Kalman Filtering (KF) approach and second approach discusses about the observer-based adaptive detection methodology (O-ADM). The IpDFT-KF method integrates spectral analysis with dynamic state estimation, utilizing the computational efficiency of the IpDFT for estimation of power system variables like frequency, phase, and magnitude. The KF ensures noise is filtered while the RoCoF is estimated. The O-ADM alternatively employs a Lyapunov-based algorithm for designing adaptive observer framework to offset the measurement distortions, such as harmonics, ensuring high accuracy and robustness even under non-Gaussian noise and extreme grid conditions. Both these methods have been validated on a 16-machine, 68-bus benchmark system, demonstrating their effectiveness in handling noise and sudden large disturbances. The errors in the frequency and RoCoF estimation were reducing as low as 0.5% even under high noise levels up to 15%. Thus, the proposed approaches can be used as viable solutions for real-time power system monitoring, enhancing grid resilience, and improving the performance of control and protection frameworks in the current networks dominated by power-electronics.
Adaptive observer, Discrete Fourier transform, Instrument transformers, Kalman filtering, Rate of change of frequency, State estimation
87-113
Mir, Abdul Saleem
491bb457-cbe5-4705-ab36-860b78763332
Singh, Abhinav Kumar
6df7029f-21e3-4a06-b5f7-da46f35fc8d3
Jamsheed, Faisal
530b2675-118b-4a56-b761-4b9a96a3cd55
20 January 2026
Mir, Abdul Saleem
491bb457-cbe5-4705-ab36-860b78763332
Singh, Abhinav Kumar
6df7029f-21e3-4a06-b5f7-da46f35fc8d3
Jamsheed, Faisal
530b2675-118b-4a56-b761-4b9a96a3cd55
Mir, Abdul Saleem, Singh, Abhinav Kumar and Jamsheed, Faisal
(2026)
Robust estimation of frequency and RoCoF in modern power systems.
In,
Shahnia, Farhad, Liu, Yilu and Pegoraro, Paolo Attilio
(eds.)
Power System Inertia, Strength, and RoCoF.
(Power Systems, Part F1350)
Springer Singapore, .
(doi:10.1007/978-981-95-3708-2_4).
Record type:
Book Section
Abstract
The extent in the estimation of frequency and rate of change of frequency (RoCoF) plays an important role in providing power system stability, preventing equipment damage, and thus ensuring reliability of the grid. The inevitable shift from synchronous generators to inverter dependent generation has substantially reduced the overall system inertia which causes rapid frequency variations reflecting in the RoCoF where it fluctuates up to ±1 Hz/s. This range of fluctuations can cause relay malfunctions leading to cascading failures in the system. This chapter discusses two advanced methodologies to address such challenges, namely the interpolated discrete Fourier transform (IpDFT) with Kalman Filtering (KF) approach and second approach discusses about the observer-based adaptive detection methodology (O-ADM). The IpDFT-KF method integrates spectral analysis with dynamic state estimation, utilizing the computational efficiency of the IpDFT for estimation of power system variables like frequency, phase, and magnitude. The KF ensures noise is filtered while the RoCoF is estimated. The O-ADM alternatively employs a Lyapunov-based algorithm for designing adaptive observer framework to offset the measurement distortions, such as harmonics, ensuring high accuracy and robustness even under non-Gaussian noise and extreme grid conditions. Both these methods have been validated on a 16-machine, 68-bus benchmark system, demonstrating their effectiveness in handling noise and sudden large disturbances. The errors in the frequency and RoCoF estimation were reducing as low as 0.5% even under high noise levels up to 15%. Thus, the proposed approaches can be used as viable solutions for real-time power system monitoring, enhancing grid resilience, and improving the performance of control and protection frameworks in the current networks dominated by power-electronics.
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Robust Estimation of Frequency and RoCoF in Modern Power Systems
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Power System Inertia, Strength, and RoCoF
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Published date: 20 January 2026
Keywords:
Adaptive observer, Discrete Fourier transform, Instrument transformers, Kalman filtering, Rate of change of frequency, State estimation
Identifiers
Local EPrints ID: 512455
URI: https://eprints.soton.ac.uk/id/eprint/512455
ISSN: 1612-1287
PURE UUID: e4ea08df-f727-4365-90a3-4e4f4c508284
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Date deposited: 30 Jun 2026 16:49
Last modified: 13 Sep 2026 15:49
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Contributors
Author:
Abdul Saleem Mir
Author:
Abhinav Kumar Singh
Author:
Faisal Jamsheed
Editor:
Farhad Shahnia
Editor:
Yilu Liu
Editor:
Paolo Attilio Pegoraro
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