Research On Power Signal Parameter Estimation Algorithm In Sudden Change Environment

The frequency,amplitude,and phase angle of the power signal reflect the operating status of the power system at each moment.Quickly and accurately obtaining the frequency,amplitude,and phase angle of the power signal can help the power department understand the operating status of each part of the power grid,which is of great significance for maintaining the safe and stable operation of the power system.The power signal of the distribution network has the characteristics of sudden change.When the current power signal parameter estimation method is applied to the sudden change of the power signal parameter estimation,it does not perform well in terms of real-time performance and estimation accuracy.In recent years,the strong tracking Kalman filter algorithm has been introduced into the power grid and used for power signal parameter estimation.Due to its characteristics of simple calculation,good convergence and strong robustness,it has developed rapidly.This article focuses on how to quickly and accurately track the power signal parameters after sudden change.The main contents include:First,linear Kalman filter algorithm and their improved extended Kalman,strong tracking Kalman,and unscented Kalman filter algorithms are introduced in detail,and the advantages and disadvantages of various algorithms are pointed out.Then,the traditional strong tracking unscented Kalman filter algorithm is introduced to calculate the fade factor.The weakening factor is usually selected according to the empirical value.When the power signal parameters are abruptly changed,the power signal parameter estimation accuracy may be low or even the filter may diverge.Aiming at the problem of weakening factor selection,a central difference algorithm is used to solve the fading factor,and it is used to detect the sudden change of power signal parameters.The value of the weakening factor is adaptively adjusted.In addition,the traditional algorithm needs to perform three lossless transformations in the calculation process,which has a large amount of calculation and is easy to cause filtering divergence.The state equation of the power signal model is a linear equation and the measurement equation is a non-linear equation.The fading factor in the calculation process is introduced into the solved sigma point set and the output covariance matrix.Based on this,a modified strong tracking unscented Kalman filter algorithm is proposed.Finally,through computer simulation and actual data obtained from a three-phase electrical power standard source,the performance of the proposed algorithm in terms of calculation time,convergence speed,and estimation accuracy in a single iteration is verified respectively,and compared with traditional algorithms.The effectiveness of the proposed algorithm is verified.