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Nonlinear dynamic model evaluation from disturbance measurements
132
Citations
19
References
2001
Year
Nonlinear System IdentificationDisturbance MeasurementsEngineeringSmart GridDynamic AnalysisSystems EngineeringNonlinear Nonsmooth NatureDisturbance DetectionPower System DynamicsTrajectory Sensitivity AnalysisPower System DynamicSystem IdentificationVibration ControlPower SystemsPower System AnalysisStability
The nonlinear nonsmooth nature of power system dynamics complicates the process of validating system models from disturbance measurements. This paper uses a Gauss-Newton method to compute a set of model parameters that provide the best fit between measurements and model response. Trajectory sensitivities are used to identify parameters that can be reliably estimated from available measurements. An overview of trajectory sensitivity analysis is provided. An example based on the Nordel system is used throughout the paper to illustrate the various concepts. This example exhibits both soft and hard nonlinearities.
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