Evaluation of Power System Identification Methods and Their Applicability for Online PSS Tuning

    Research output: Chapter in Book or Conference ProceedingsConference Proceedings with Oral Presentationpeer-review


    This paper compares four methods and their accuracy in the identification of a simplified power system model.
    The identified model is to be used for power system stabilizer (PSS) tuning. Therefore, the focus is on identifying a low-order linear model that is able to accurately capture the dynamics of the system in the frequency bandwidth in which the PSS has typically to act in order to damp low frequency oscillations.
    We evaluate polynomial transfer function models and state space model structures under different estimation methods are considered. The two-area four-generator power system model is used as test case, and the results of the four methods are compared to the analytical results in terms of both low-frequency oscillation modes and frequency response in the 0.1 - 2Hz interval.
    The combination of the Predictor Based Subspace IDentification (PBSID) method and the Prediction-Error Minimization (PEM) method showed the better performance.
    Original languageEnglish
    Title of host publication2023 IEEE Belgrade PowerTech
    Place of PublicationBelgrade
    Number of pages7
    Publication statusPublished - 2023
    Event 2023 IEEE Belgrade PowerTech - Belgrade, Serbia
    Duration: 25 Jun 202329 Jun 2023


    Conference 2023 IEEE Belgrade PowerTech

    Research Field

    • Power System Digitalisation


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