A comparative study on different power system frequency estimation techniques. (18th May 2009)

• Record Type: Journal Article
• Authors: Subudhi, B.; Ray, P.K.; Mohanty, S.R.; Panda, A.M.
• Is Part Of: International journal of automation and control. Volume 3:Number 2/3(2009)
• Page Start: 202
• Page End: 215
• Publication Date: 2009-05-18
• Subjects: ELS technique -- extended least squares -- Kalman filter -- LMS technique -- least mean squares -- covariance matrix -- correlation matrix -- system structure matrix -- observation vector -- frequency estimation -- power system parameters; Automation -- Periodicals; Control theory -- Periodicals; Automatic control -- Periodicals; Robots -- Periodicals; Bionics -- Periodicals; Intelligent control systems -- Periodicals
• Languages: English
• ISSNs: 1740-7516

Abstract

This paper presents the estimation of frequency which is an important power system parameter by Extended Least Square (ELS) technique. The above technique is validated by comparing its performance with the existing techniques such as Kalman Filter (KF) and Least Mean Square (LMS) technique, etc. Using different simulation studies with signals having different signal to noise ratio values and with step change in frequency, it is observed that ELS technique outperforms over LMS and KF methods on power system frequency estimation. Initialisation of covariance matrix in KF method and complicacy due to incorporation of correlation matrix in LMS algorithm affect their convergence. But ELS algorithm becomes very simple and attractive due to the absence of covariance and correlation matrix.