Lars,

I recall some research on dual-sampling of power systems in the context of adaptive control and protection. But that was way back, and if I recall right, did not make much headway...

-Sanjay

What is the reason to use something that slow, than estimate - if pretty much every hardware today can sample and process much more data? Can you point me on some of that explanations? And what do you mean by low frequency AC system?

You can visit this link for having concepts of non-uniform sampling

https://smartech.gatech.edu/bitstream/handle/1853/45873/luo_chenchi_201212_phd.pdf

Hello,

You can see:

J. A. de la O Serna, "Synchrophasor Estimation Using Prony's Method," in IEEE Transactions on Instrumentation and Measurement, vol. 62, no. 8, pp. 2119-2128, Aug. 2013.

doi: 10.1109/TIM.2013.2265436

keywords: {damping;filtering theory;frequency estimation;phasor measurement;power system stability;Prony filters;Prony method;adaptive approximation;closed signal model;dynamic phasor estimator;finite time interval;one-cycle Fourier filter;power system stability;static signal model;synchrophasor estimation;time window;Dynamic phasor estimates;Prony's method;frequency estimates;phasor measurement unit;power system oscillations;synchrophasors},

URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6544683&isnumber=6556973

with the following papers you can achieve it:

J. A. de la O Serna, J. M. Ramirez, A. Zamora Mendez and M. R. A. Paternina, "Identification of Electromechanical Modes Based on the Digital Taylor-Fourier Transform," in IEEE Transactions on Power Systems, vol. 31, no. 1, pp. 206-215, Jan. 2016.

doi: 10.1109/TPWRS.2015.2403290

keywords: {Fourier transforms;channel bank filters;power engineering computing;power system faults;power system identification;signal reconstruction;spectral analysis;time-frequency analysis;DTFT;digital taylor-Fourier transform;filter bank;instantaneous damping;low-frequency electromechanical mode identification;monocomponent signal extraction;nonlinear signal time-frequency analysis;power system;signal decomposition;signal reconstruction;sliding-window data;spectral analysis;Damping;Discrete Fourier transforms;Frequency estimation;Harmonic analysis;Oscillators;Power system dynamics;Digital Taylor-Fourier transform;electromechanical modes;power oscillations;ringdown analysis;signal decomposition},

URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7050382&isnumber=7361773

J. A. de la O Serna, "Taylor–Fourier Analysis of Blood Pressure Oscillometric Waveforms," in IEEE Transactions on Instrumentation and Measurement, vol. 62, no. 9, pp. 2511-2518, Sept. 2013.

doi: 10.1109/TIM.2013.2258245

keywords: {Fourier analysis;Fourier transforms;cardiology;critical points;pneumodynamics;power systems;DTFT envelope estimation;Taylor components;Taylor order model;amplitude modulated nonlinear signals;blood pressure oscillometric waveforms;breathing activity;cardiac frequency;critical points;diastolic blood pressure assignment;digital Taylor-Fourier transform;frequency fluctuations;harmonic separation;oscillating harmonics;oscillating power systems;phase derivative estimation;phasor estimation;signal model;systolic blood pressure assignment;Biorthogonal filter banks;Mayer waves;blood pressure oscillometric waveforms;digital Taylor–Fourier transform (DTFT);harmonic analysis;oscillations},

URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6527355&isnumber=6576154

Best regards,

Mario