An Integrated Assessment Method for Power System Transient Stability Considering PMU Data Loss

The widespread deployment of phasor measurement units (PMUs) provides the possibility for data-driven transient stability assessment (TSA) methods. However, missing PMU measurement data can significantly reduce the performance of the assessment model. To address this issue, an integrated transient stability assessment method for power systems considering PMU data loss is proposed. First, an optimal collection of PMU clusters, which ensures the observability of all system buses, is constructed based on feature importance. Then, transient stability sub-classifiers are trained using feature sets corresponding to the PMU clusters. Finally, an adaptive weighted fusion method is used to build the integrated transient stability assessment model for PMU failure scenario. Simulations on the modified IEEE 39-bus system with renewable energy source demonstrate that the proposed method can still provide high accuracy results in the event of PMU failures and data loss, while also offering strong robustness against noise interference.