Probabilistic ranking of critical parameters affecting voltage stability in network with renewable generation

This paper introduces a probabilistic method for the ranking of influential uncertain parameters for the accurate assessment of power system voltage stability. Future power systems will be highly interconnected and complex with a variety of uncertain parameters such as the injection of intermittent renewable energy resources, the adoption of flexible hierarchical control structures and the appearance of new types of loads. Identifying and ranking the uncertain parameters are important in future power system operations since they can provide referable indexes for system operators to achieve better system management with less monitoring. This paper presents the probabilistic method for the identification and ranking of critical uncertain parameters. A modified version of the 68 bus NETS-NYPS test system is used in this study for simulation studies. The effects of uncertain parameters are modelled with Monte-Carlo method in the environments of MATLAB and DIgSILENT PowerFactory. The performances of the `nose-point area' of P-V Curves for system load buses are used as indexes when evaluating their sensibility for specific uncertainties.