A Comparative Study of Polynomial Chaos Expansion-Based Methods for Global Sensitivity Analysis in Power System Uncertainty Control

In this brief, we compare three polynomial chaos expansion (PCE)-based methods for ANCOVA (ANalysis of COVAriance) indices based global sensitivity analysis for correlated random inputs in two power system applications. Surprisingly, the PCE-based models built with independent inputs after decorrelation may not give the most accurate ANCOVA indices, though this approach seems to be the most correct one and was applied in Caniou (2012) in the field of civil engineering. In contrast, the PCE model built using correlated random inputs directly yields the most accurate ANCOVA indices for global sensitivity analysis. These results provide important guidance for uncertainty management and control in power system operation and security assessment.