Uncertainty Quantification (UQ) is explored in the context of appropriate sampling of measurements. It is established that a statistical one-on-one relationship between the source of randomness and measurement data is possible only when the data is sampled appropriately. Unlike most of the methods in the literature, the proposed Uncertainty Quantification is thus independent of the modelling details of the power system as well as the knowledge of time-varying disturbances affecting the system. Various case scenarios have been demonstrated using the IEEE 9-bus system as test system to investigate the performance of the proposed technique.


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    Titel :

    Data-Driven Uncertainty Quantification in Stochastic Power Systems


    Beteiligte:
    Thakur, Suravi (Autor:in) / Mushtaq, Hafsah (Autor:in) / Senroy, Nilanjan (Autor:in)


    Erscheinungsdatum :

    31.07.2024


    Format / Umfang :

    2025899 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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