Existing Approaches and Trends in Uncertainty Modelling and Probabilistic Stability Analysis of Power Systems with Renewable Generation

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    Abstract

    The analysis of power systems with a significant share of renewable generation using probabilistic tools is essential to appropriately consider the impact that the variability and intermittency of the renewable generation has on the grid. This paper provides a critical assessment and classification of the available probabilistic computational methods that have been applied to power system stability assessment (including small and large disturbance angular stability, voltage and frequency stability). A probabilistic analysis framework with a state-of-the-art review of the existing literature in the area is presented comprising of a review of (i) input variable modelling, (ii) computational methods and (iii) presentation techniques for the output/results. The most widely used probabilistic methods in power system studies are presented with their specific application areas, advantages, and disadvantages. The purpose of this overview, classification, and assessment of the existing methods is to identify the most appropriate probabilistic methods to be used in their current forms, or suitably modified, for different types of stability studies of power systems containing renewable generation.
    Original languageEnglish
    Pages (from-to)168-180
    Number of pages13
    JournalRenewable & Sustainable Energy Reviews
    Volume101
    Early online date19 Nov 2018
    DOIs
    Publication statusPublished - Mar 2019

    Keywords

    • Power system computing
    • Power system stability
    • Probabilistic assessment
    • Computational efficiency
    • renewable energy
    • Uncertainty
    • Renewable energy

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