Dynamic parameter estimation of generators
Abstract
Various examples are provided for parameter estimation of generators. In one example, among others, a method includes collecting data corresponding to a generator using a phasor management unit (PMU) and estimating dynamic parameters of the generator using extended Kalman filtering (EKF) and the collected PMU data. In another example, a system includes at least one application executable in a processing device that obtains operational data corresponding to a generator and estimates a dynamic parameter of the generator using EKF and the operational data. In another example, an EKF estimator includes a dynamics estimator configured to estimate a state variable of a generator, a geometry estimator configured to estimate phasor values associated with the generator, and a Kalman filter gain configured to determine a correction to the state variable.
- Inventors:
- Issue Date:
- Research Org.:
- Univ. of South Florida, Tampa, FL (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1568082
- Patent Number(s):
- 10234508
- Application Number:
- 13/968,693
- Assignee:
- University of South Florida (Tampa, FL)
- Patent Classifications (CPCs):
-
G - PHYSICS G01 - MEASURING G01R - MEASURING ELECTRIC VARIABLES
H - ELECTRICITY H02 - GENERATION H02K - DYNAMO-ELECTRIC MACHINES
- DOE Contract Number:
- OE0000369
- Resource Type:
- Patent
- Resource Relation:
- Patent File Date: 08/16/2013
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Miao, Zhixin, and Fan, Lingling. Dynamic parameter estimation of generators. United States: N. p., 2019.
Web.
Miao, Zhixin, & Fan, Lingling. Dynamic parameter estimation of generators. United States.
Miao, Zhixin, and Fan, Lingling. Tue .
"Dynamic parameter estimation of generators". United States. https://www.osti.gov/servlets/purl/1568082.
@article{osti_1568082,
title = {Dynamic parameter estimation of generators},
author = {Miao, Zhixin and Fan, Lingling},
abstractNote = {Various examples are provided for parameter estimation of generators. In one example, among others, a method includes collecting data corresponding to a generator using a phasor management unit (PMU) and estimating dynamic parameters of the generator using extended Kalman filtering (EKF) and the collected PMU data. In another example, a system includes at least one application executable in a processing device that obtains operational data corresponding to a generator and estimates a dynamic parameter of the generator using EKF and the operational data. In another example, an EKF estimator includes a dynamics estimator configured to estimate a state variable of a generator, a geometry estimator configured to estimate phasor values associated with the generator, and a Kalman filter gain configured to determine a correction to the state variable.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {3}
}
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