Robust Probabilistic Analysis of Transmission Power Systems based on Equivalent Circuit Formulation
For power system researchers, this work offers a more robust method for probabilistic contingency analysis, but the contribution is incremental as it applies an existing method to a new application.
This paper applies a robust equivalent split-circuit approach to probabilistic power flow analysis, using Simple Random Sampling Monte Carlo for contingency analysis. Results on two public test cases show improved robustness over standard power flow tools.
Recent advances in steady-state analysis of power systems have introduced the equivalent split-circuit approach and corresponding continuation methods that can reliably find the correct physical solution of large-scale power system problems. The improvement in robustness provided by these developments are the basis for improvements in other fields of power system research. Probabilistic Power Flow studies are one of the areas of impact. This paper will describe a Simple Random Sampling Monte Carlo approach for probabilistic contingency analyses of transmission line power systems. The results are compared with those from Monte Carlo simulations using a standard power flow tool. Lastly, probabilistic contingency studies on two publicly available power system cases are presented.