A Fast Method for Uncertainty Analysis of Power System Dynamic Simulation

Uncertain variables, such as electric power system parameters, have significant impacts on dynamic simulations of systems. As traditional uncertainty analysis methods for simulations, both the simulation method and approximation are difficult to balance model complexity, computational efficiency, accuracy. In order accuracy, this paper proposes a based Nataf transformation Gaussian-Hermite quadrature. Firstly, samples normal distribution space determined according quadrature points transformation. Secondly, obtain by inverse transformation, perform simulation. Thirdly, random output is approximated linear combination single input, mean standard deviation under impact input calculated Then, calculate all input. Finally, effectiveness proposed validated IEEE 9-bus 39-bus system. Compared with Monte Carlo Latin Hypercube sampling, can greatly reduce time uncertain while maintaining high