Transient Stability-Constrained Optimal Power Flow Model Based on CatBoost-DF and ISOA

Traditional transient stability-constrained optimal power flow (TSCOPF) methods rely on solving complex nonlinear differential equations, resulting in high computational demands and lengthy processing times. To address these issues, this paper proposes a TSCOPF model based on a cascaded CatBoost model (CatBoost-DF) and an improved seagull optimization algorithm (ISOA). First, a TSCOPF model is constructed. Second, the CatBoost-DF model is developed to establish a mapping relationship between the dynamic characteristics of the power system and the power angle of generators. The trained CatBoost-DF model is then employed as a surrogate model to handle transient stability constraints, thereby avoiding the computation of complex differential-algebraic equations traditionally required in transient stability constraint analysis. Then, the ISOA is employed to iteratively solve the TSCOPF model. This enables timely adjustment of generator output when transient instability risks arise, preventing accidents while maintaining system economic efficiency. Finally, simulations conducted on the IEEE 39 bus system demonstrate that this method effectively safeguards both system security and economic performance.