Comparison of Recursive Parameter Identification Techniques for Computer Control of Power Systems

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Comparison of Recursive Parameter Identification Techniques for Computer Control of Power Systems

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dc.contributor.author Sheirah, M. A. en_US
dc.date.accessioned 2009-11-25T13:04:48Z
dc.date.available 2009-11-25T13:04:48Z
dc.date.issued 1988 en_US
dc.identifier.citation Engineering Journal of Qatar University, 1988, Vol. 1, Pages 243-262. en_US
dc.identifier.uri http://hdl.handle.net/10576/7897
dc.description.abstract This paper outlines the main features of parameter identification in electric power systems. A series of recursive parameter identification techniques is presented, this containing the generalized — and extended least square techniques, the recursive maximum likelihood technique, the stochastic approximation method, and the gradient technique. These identification techniques are tested using a model of the interconnected power system of two areas to illustrate the applicability of discrete parameter identification for on-line computer control of power systems. The area control errors are considered as the controlled variables (system outputs). The changes in the governor gate position are the manipulated variables, and the variations in load are the disturbances. To evaluate the performance of the identification technique the integral of the error-squares criteria is used. This error is defined as the difference between the actual system output and the identified model output. A real time package to simulate the system and model of the identification techniques is designed and the performance of the system is recorded. PBRS is used as standard test signal during this study. en_US
dc.language.iso en en_US
dc.publisher Qatar University en_US
dc.subject Control & Simulation en_US
dc.title Comparison of Recursive Parameter Identification Techniques for Computer Control of Power Systems en_US
dc.type Article en_US
dc.identifier.pagination 243-262 en_US
dc.identifier.volume 1 en_US

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