Detecting electromechanical oscillations in power systems
First Claim
1. Method of detecting electromechanical oscillations in power systems, wherein a) a system quantity of the power system is repeatedly measured and a series of measured values of the system quantity is generated, b) parameters of a parametric model are estimated from said series, c) information about an electromechanical oscillation mode of the power system are deduced from the parameters, wherein d) said parameters are updated every time a new value of the system quantity is measured.
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Abstract
The detection of electromechanical oscillations in power systems and the estimation of their parameters (frequency ƒ and damping ξ) is based on a linear time-varying model. The parameters of the linear model are on-line adapted by means of Kalman filtering techniques to approximate the measured signal y (representing the behaviour of the power system) optimally in the sense of a quadratic criterion. The estimated model parameters are then the basis for the calculation of parameters of the oscillations. Adaptive algorithms are based on a recursive calculation of the estimated parameter vector for each time-step based on the new value of the measured signal and the old values of the estimated parameters. As opposed to the collection of data over a time window and then performing the parameter identification at once, any change in the system can thus be detected much faster.
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10 Claims
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1. Method of detecting electromechanical oscillations in power systems, wherein
a) a system quantity of the power system is repeatedly measured and a series of measured values of the system quantity is generated, b) parameters of a parametric model are estimated from said series, c) information about an electromechanical oscillation mode of the power system are deduced from the parameters, wherein d) said parameters are updated every time a new value of the system quantity is measured.
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