Integrated Assessment of Transient Angle Stability and Voltage Stability Considering Renewable Energy Sources

Transient angle instability and transient voltage instability often occur simultaneously and interact with each other, which increases the difficulty of stability assessment and emergency control. To achieve comprehensive guidance for emergency control through stability assessment, an instability mode recongnition method is proposed. This method describes the fault severity using the critical fault clearing time, characterizes the dominance of angle instability and voltage instability based on their occurrence order, and quantifies the coupling degree with the time difference between them. A four-quadrant instability mode recongnition diagram is constructed. To achieve the integrated online assessment, an improved convolutional neural network (CNN) model based on the convolutional block attention module (CBAM) is developed, and a two-stage integrated stability assessment scheme is proposed based on this model. Finally, the New England 10-machine 39-bus system is used for simulation verification, and the results show that the proposed method can achieve comprehensiveness, effectiveness and accuracy. Further, the applicability of the proposed method in systems with renewable energy is demonstrated using a modified 10-machine 39-bus system incorporating renewable energy.