Towards an Uncertainty-Based Model Level Selection for the Simulation of Complex Power Systems

The paper reviews the current situation in the development of tools supporting the design of modern power systems. Many simulation scenarios require analyzing the same topology with different level of details. As result, it is becoming more and more important to define automatic procedures able to select the appropriate detail for a model given a simulation task. The authors introduce here the idea of using a criterion based on uncertainty propagation. The proposed approach synthesizes the difference between two model levels through a stochastic analysis in the time-domain. The concept is demonstrated with the help of a reference example in power systems.