Bounding uncertainty in power system dynamic simulations

Parameters of power system models can never be known exactly. Yet dynamic security assessment relies upon the simulations derived from those uncertain models. This paper proposes an approach to quantifying the uncertainty in simulations of power system dynamic behaviour. It is shown that trajectory sensitivities can be used to generate an accurate first order approximation of the trajectory corresponding to a perturbed parameter set. The computational cost of obtaining the sensitivities and perturbed trajectory is minimal. Therefore it is feasible to quickly generate many approximate trajectories from a single nominal case. To quantify the effect of parameter uncertainty on the nominal case, parameter sets are randomly generated according to their underlying statistical distribution. An approximate trajectory is obtained for each set. The collection of trajectories provides a bound within which the actual system dynamic behaviour should lie.