Improved Recursive Newton Type Algorithm based power system frequency estimation

This paper presents power system frequency estimation by using an Improved Recursive Newton Type (IRNTA) algorithm. The proposed approach uses Jacobian and covariance matrices for updating the unknown parameters. The recursive form of unknown parameters and covariance matrix are incorporated in the algorithm to have faster convergence. The performance of the proposed algorithm is studied through simulations and experiments for several critical cases that often arise in a power system. Efficacy of the proposed algorithm is also compared with other signal processing techniques such as Recursive Least Square (RLS) and Kalman Filter (KF). Studies made on industrial data also support for the superiority of the proposed algorithm.