Key Feature Selection Method for Intelligent Assessment of Transient Power Angle Stability based on Physical Mechanism and Improved Relief

Key feature selection is of great significance for intelligent assessment of transient power angle stability of power system. This paper proposes a key feature selection method combining physical mechanism and improved Relief. The Relief index reflects the strength of the feature to classify transient power angle stability and instability. By eliminating redundancy and increasing the weight of unstable samples, the accuracy of index calculation and the ability to adapt to sample imbalance are improved. Through the combination of physical mechanism and improved Relief, the key feature quantities reflecting the stability of transient angle can be comprehensively selected by iterative optimization, and the problem of missing selection of key feature parameters under complex transient stability can be solved. The effectiveness of the method is verified by an actual power grid example.