A contingency selection approach considering uncertainty based on interval theory

The Static Security Assessment of power system is affected by the uncertainty of the power flow distribution introduced by renewable resources. In this paper, a fast contingency selection approach considering load and generation uncertainties is proposed. Firstly, a linearized interval power flow algorithm is developed for post-contingency simulation. Then, an interval number comparison method based on Bayesian Theory is applied in interval contingency index comparison. Finally, an approximately consistent ranking method is introduced to contingency ranking. The effectiveness of the proposed approach is demonstrated by applying it to contingency selection for several IEEE standard test systems and two practical provincial power grids in China. Simulation results indicate that the proposed approach is computationally light and highly accurate under uncertainties.