NDLI: SG parameters estimation based on synchrophasor data

Content Provider	IET Digital Library
Author	Shooshtari, Babak Ahmadzadeh Torkzadeh, Roozbeh Kordi, Meysam Marzooghi, Hesamoddin Eghtedarnia, Fariborz
Abstract	In this study, first, it is shown that the least-squares (LS) algorithm outperforms well known methods such as extended Kalman filter and unscented Kalman filter for synchronous generator (SG) parameters estimation using phasor measurement unit (PMU) data. However, as the LS algorithm may estimate the SG parameters inaccurately if the initial values of SG model state variables are not valid, a modified LS (MLS) algorithm, which estimates the initial values of SG model state variables alongside SG parameters, is proposed. In addition to parameters estimation of an SG classical model, the performance of this algorithm in the estimation of whole electromagnetic parameters and rotor inertia constant of an SG full-order model is evaluated. Note that conventionally, measurements of generators rotor angles were used to estimate SGs full-order model parameters; nevertheless, in the proposed MLS algorithm, online SG parameters estimation is accomplished using PMU data without relying on rotor angle measurement that is difficult to be obtained in practise. Simulation results demonstrate the effectiveness of the proposed algorithm in SG parameters estimation for various disturbances and noisy measurements. Furthermore, the effect of mechanical torque signal unavailability on the proposed algorithm capability is studied, where the efficacy of this algorithm is proven.
Starting Page	2958
Ending Page	2967
Page Count	10
ISSN	17518687
Volume Number	12
e-ISSN	17518695
Issue Number	Issue 12, Jul (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-gtd/12/12
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2017.1989
Journal	IET Generation, Transmission & Distribution
Publisher Date	2018-04-04
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Angular Measurement Electromagnetic Parameter Extended Kalman Filter Generator Rotor Angle Measurement Interpolation And Function Approximation Least Squares Approximation Mechanical Torque Signal MLS Algorithm Modified Least-square Method Numerical Analysis Parameter Estimation Phasor Measurement Phasor Measurement Unit PMU Power System Measurement And Metering Power System Planner Power System Planning Power System Planning And Layout Rotor Inertia Constant Rotors SG Full-order Model SG Parameter Estimation Spatial Variables Measurement Statistics Synchronous Generator Synchronous Machine Synchrophasor Data Unscented Kalman Filter
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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