Improved Recursive Newton Type Algorithm based power system frequency estimation

被引：8

作者：

Ray, Pravat Kumar ^{[1
]}

Puhan, Pratap Sekhar ^{[2
]}

Panda, Gayadhar ^{[3
]}

机构：

[1] NIT Rourkela, Dept Elect Engg, Rourkela, Orissa, India

[2] BIET Bhadrak, Dept Elect Engg, Bhadrak, Orissa, India

[3] NIT Meghalaya, Dept Elect & Elect Engg, Shillong, Meghalaya, India

来源：

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS | 2015年 / 65卷

关键词：

Power system frequency estimation; Fast Fourier Transform (FFT); Least Square (LS); Recursive Least Square (RLS); Kalman Filter (KF); Improved Recursive Newton Type Algorithm (IRNTA); KALMAN-FILTER; HARMONIC ESTIMATION; IDENTIFICATION; SIGNALS;

D O I：

10.1016/j.ijepes.2014.10.017

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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. (C) 2014 Elsevier Ltd. All rights reserved.

引用

页码：231 / 237

页数：7

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