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State-space model parameter identification in large-scale power systems
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DOI：10.1109/TPWRS.2008.922632.png)
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Abstract
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A hierarchical method for model parameter identification of large-scale power systems is suggested in this paper. The method uses the theoretical relations between machine parameters and the other network elements to find the state-space model of the system. The hierarchical structure consists of two levels. In the first level, the local subsystem parameters are estimated using online measurements. In the second level, by transferring some information from each subsystem to a global coordinator, the interaction parameters are identified. The obtained state-space model parameters can be converted to the physical parameters of the synchronous generators. The identified model is useful for controller design and stability tests. The proposed identification method is applied to a sample power system which consists of five subsystems. The simulation results show accuracy of the identified model.
Keywords:
identification
interconnected power systems
large-scale systems
power system modeling
state-space methods
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