Transient Stability Assessment Based on Parallel Hidden Markovian Mode in Power System

The significant error in transient stability assessment during power system operation leads to a prolonged response time for emergency control during unstable system states. This research utilizes a PHMM (Parallel Hidden Markov model) for transient assessment to categorize the collected system data into two states: unstable and stable. A discriminant-based emergency control strategy is then employed to shorten the response time by selecting appropriate actions. The system's need for emergency control is further analyzed by determining the presence of convex trajectories. Finally, the transient stability assessment of the system is modeled using a MCG (Multi-granularity Cascaded Gradient) evaluation algorithm, enhancing the reliability of the assessment results. Experimental results demonstrate that this approach effectively reduces errors to 0.68% in transient stability assessment and shortens the response time to 1.67s during system instability.