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    Item type:Publication,
    On solving probabilistic load flow for radial grids using polynomial chaos
    (IEEE, 2017)
    Appino, Riccardo R.
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    Mühlpfordt, Tillmann
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    The uncertain nature of electric energy production from distributed generation based on renewable resources has to be considered when managing and operating distribution grids. In several cases, this uncertainty can be described using non-Gaussian random variables, requiring appropriate probabilistic load flow techniques. The present paper proposes a method that, exploiting Polynomial Chaos Expansion and Galerkin projection, allows a reformulation of the probabilistic load flow for radial grids as an enlarged deterministic problem. For radial grids, the well known Backward-Forward-Sweep method is applicable. This method does not require any model simplification or assumptions on the probability density function of the input random variables, i.e. it is applicable to non-Gaussian uncertainties. We draw upon a real 84-node grid and compare results against those obtained from Monte Carlo simulation.
    Publicationtype: Conference Paper
      6
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    Item type:Publication,
    Distributed two-stage network topology processor for HVDC grid operation
    This paper presents the results of an analysis of distributed two-stage coordination of network topology processor for HVDC grids. In the first stage of the two-stage processor, the substation topology is analyzed locally using an automated graph-based algorithm. Thereafter, a distributed algorithm is proposed to used the neighboring information to realize the grid connectivity. For distributed islanding detection, the connectivity problem is formulated as a set of linear equations and solved iteratively using successive-over-relaxation method. The performance of the proposed methods versus conventional one-stage method has been tested in an islanding scenario for a 5-terminal HVDC grid.
    Publicationtype: Conference Paper
      41