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dc.contributor.authorSubudhi, B-
dc.contributor.authorRay, P K-
dc.contributor.authorMohanty, S R-
dc.contributor.authorPanda, A M-
dc.identifier.citationInternational Journal of Automation and Control, Volume 3, Nos. 2/3, 2009en
dc.description.abstractThis 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.en
dc.format.extent265694 bytes-
dc.subjectELS techniqueen
dc.subjectextended least square techniqueen
dc.subjectLMS techniqueen
dc.subjectleast mean square techniqueen
dc.subjectcovariance matrixen
dc.subjectcorrelation matrixen
dc.subjectsystem structure matrixen
dc.subjectobservation vectoren
dc.subjectfrequency estimationen
dc.subjectpower system parametersen
dc.titleA Comparative Study on Different Power System Frequency Estimation Techniquesen
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