Nonintrusive Uncertainty Quantification of Dynamic Power Systems Subject to Stochastic Excitations

Continuous-time random disturbances (also called stochastic excitations) due to increasing renewable generation have an impact on power system dynamics; However, except from the slow Monte Carlo simulation, most existing methods for quantifying this are intrusive, meaning they not based commercial simulation software and hence difficult use utility companies. To fill gap, paper proposes efficient nonintrusive method uncertainty in dynamic systems subject excitations. First, Gaussian or non-Gaussian excitations modeled with Itô process as differential equations. Then, is spectrally represented by independent parameters, which enables polynomial chaos expansion (PCE) of response be calculated via adaptive sparse probabilistic collocation method. Finally, probability distribution high-order moments performance index accurately efficiently quantified. The proposed such PSS/E carefully designed input signals, ensures ease validated case studies IEEE 39-bus 118-bus test systems.