Risk assessment of power system transient instability incorporating renewable energy sources

Transient stability affected by renewable energy sources integration due to reductions of system inertia and uncertainties associated with the expected generation. The ability manage relation between available big data transient assessment (TSA) enables fast accurate monitoring TSA prepare required actions for secure operation. This work aims build a predictive model using Gaussian process regression online utilizing selected features. critical fault clearing time (CCT) is used as index. features map dynamics reduce burden collection computation time. were collected offline from power flow calculations at different operating conditions. Therefore, CCT was calculated electromagnetic transientsimulation each point applying self-clearance three phase short circuit prespecified locations. selection implemented neighborhood component analysis, Minimum Redundancy Maximum Relevance algorithm, K-means clustering algorithm. vulnerability tends result great variation on best methods. Hybrid common enhance refining final proposed investigated over 66-bus system.