Abstract
The paper presents a new approach to estimation of the dynamic power phasors parameters. The observed system is modelled in algebra of matrices related to its Taylor-Fourier-trigonometric series representation. The proposed algorithm for determination of the unknown phasors parameters is based on the analytical expressions for elements of the Gram’s matrix associated with this system. The numerical complexity and algorithm time are determined and it is shown that new strategy for calculation of Gram’s matrix increases the accuracy of estimation, as well as the speed of the algorithm with respect to the classical way of introducing the Gram’s matrix. Several simulation examples of power system signals with a time-varying amplitude and phase parameters are given by which the robustness and accuracy of the new algorithm are confirmed.
Highlights
The paper presents a new approach to estimation of the dynamic power phasors parameters
In accordance with the modelling method, the measurement method, the algorithms can be divided into two main classes: algorithms that rely on the pure sinusoidal signal model and algorithms based on a nonsinusoidal model [5]
The TaylorKalman method based on the Kalman observer in order to achieve nondelayed dynamic phase estimation is described in [16]
Summary
The paper presents a new approach to estimation of the dynamic power phasors parameters. The TaylorKalman method based on the Kalman observer in order to achieve nondelayed dynamic phase estimation is described in [16] This method is further enhanced by the development of the state space for harmonic infiltration in [17] and is called Tailor Fourier Kalman. A double suboptimal-scaling factor-adaptive strongtracking Kalman filter (DSTKF)-based phasor measurement unit algorithm which can meet the accuracy requirement of the IEEE standard C37.118.1 under the dynamic condition was proposed in [26]. This method uses a kth Taylor polynomial to linearize the complex exponential of the signal model and estimates the dynamic phasor using DSTKF. In [27], a combination of the least square-based Prony analysis and Taylor expansion called Taylor–Prony is proposed to estimate the dynamic phasor
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