Probabilistic Stability Assessment for Active Distribution Grids

Abstract

This paper demonstrates the concept of probabilistic stability assessment on large-signal stability in the use case of short circuits in an active distribution grid. Here, the concept of survivability is applied, which extends classical stability assessments by evaluating the stability and operational limits during transients for a wide range of operating points and failures. For this purpose, a free, open-source, and computationally efficient environment (Julia) for dynamic simulation of power grids is used to demonstrate its capabilities. The model implementation is validated against established commercial software and deviations are minimal with respect to power flow and dynamic simulations. The results of a large-scale survivability analysis reveal i) a broad field of application for probabilistic stability analysis and ii) that new non-intuitive stability correlations can be obtained. Hence, the proposed method shows strong potential to efficiently conduct power system stability analysis in active distribution grids.

Toward dynamic stability assessment of power grid topologies using graph neural networks

“…Conducting high-fidelity simulations of the whole hierarchy of the power grid and exploring all states will not be feasible. 7 For future power grids, knowledge of how to design robust dynamics is required. This has led to a renewed interdisciplinary interest in understanding the collective dynamics of power grids, 8 with a particular focus on the robustness of the self-organized synchronization mechanism underpinning the stable power flow.…”

PowerDynamics.jl -- An experimentally validated open-source package for the dynamical analysis of power grids

“…Due to Julia's just-in-time compilation, PowerDynamics has also strong performance advantages compared to simulations in MATLAB or Python. It has also been shown to be much more performant than its commercial competitors MATLAB Simulink and DIgSILENT PowerFactory [7]. This does not only enable the dynamic simulation of very large test cases with a large number of nodes but also Monte Carlo sampling based methods.…”

“…It is based on the programming language Julia [6] and developed in a collaboration between the Potsdam Institute for Climate Impact Research (PIK) and the company elena international GmbH 1 . PowerDynamics has been shown to easily beat the simulation times of common commercial simulation environments, such as PowerFactory or MATLAB Simulink [7]. This opens up the possibility to run very large test cases or apply Monte Carlo sampling based methods [8,9].…”

NetworkDynamics.jl -- Composing and simulating complex networks in Julia

“…NetworkDynamics.jl was initially developed with simulations of power systems in mind. It is the backbone of PowerDynamics.jl 22,23 , an open-source framework for dynamic power grid modeling and analysis, which has been shown to be computationally more efficient than its proprietary competitors PowerFactory and MATLAB Simulink 24 . The fundamental requirement for simulating power systems is the capability of simulating large heterogeneous dynamical systems with algebraic constraints.…”