Calculating probability of critical system states by using Bayesian distribution system state estimation

For monitoring and control applications, which are necessary to ensure safe grid operation, the knowledge of the current, possibly critical, system state is essential. In this paper the system state is estimated from a limited set of real-time measurements and additional prior knowledge. From these inputs a posterior distribution for the system state is derived by Bayes rule. Then the entire posterior distribution with uncertainty information is used to calculate the probability of critical system states due to voltage band and thermal current limit violations. The method is demonstrated for a 107 bus, 20 kV grid.