Precise algorithm for frequency estimation under dynamic and step-change conditions

To achieve fast-response frequency estimation under step-change dynamics as well as accurate frequency estimation under slowly varying dynamics, a dynamic-model-based frequency estimation with step-change detection (DFESD) algorithm is proposed in this study. In DFESD, the derivative of the initial phasor estimation, which is obtained from short-time Fourier transform and the first-order Taylor-expansion phasor model, is used to detect the step changes in signals. Then, the initial estimations are adaptively selected by the data-selection strategy to estimate the frequency, of which the estimation is based on a high-order Taylor-expansion model to express the dynamic characteristics in signal. DFESD is a Taylor-expansion-based algorithm and it avoids the states mixture of both pre- and post- step-change data within one long data window, so it can track the frequency accurately under slowly varying dynamics and give fast-response estimation under step-change dynamics. Performance of the proposed algorithm is evaluated by computer-simulated and electromagnetic transients including DC (EMTDC) generated signals, and the results prove the efficiency of DFESD for accurate or fast-response frequency estimation under various test cases.