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Parameter estimation applied to power system models subject to random disturbances

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Title: Parameter estimation applied to power system models subject to random disturbances
Author: Muller, Hans
Degree Master of Applied Science - MASc
Program Electrical and Computer Engineering
Copyright Date: 1979
Abstract: For control of an electric generator, it is desirable to approximate the remote part of the power system by a low order model, whose parameters can be estimated from measurements. The proposed model for the remote system consists of a large synchronous machine and a random varying load to account for the dynamic behaviour and for the small fluctuations that are always present. The maximum likelihood algorithm is a good method for parameter estimation of a noisy system. It can even be used for estimation from measurements alone, without applied disturbance, which could be of great advantage in a power system. The algorithm is derived in a form suitable for efficient digital processing of sampled measurements from a linear continuous system with physical parameters. The performance of the algorithm is tested by computer simulation of a simplified model for several cases of deterministic and/or stochastic input. It is demonstrated, that good estimates can be found from the output of a disturbed system when no intentional input is applied.
URI: http://hdl.handle.net/2429/21569
Series/Report no. UBC Retrospective Theses Digitization Project [http://www.library.ubc.ca/archives/retro_theses/]
Scholarly Level: Unknown

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