考虑台风时空演变的配电网灾前-灾中应急调度方法OA

Typhoon disasters severely impact the operation of distribution networks,presenting challenges such as strong randomness in prediction,difficulties in pre-disaster and in-disaster coordinated scheduling,and high computational complexity.This paper proposes an emergency scheduling method for distribution networks that considers the spatiotemporal evolution of typhoons,covering both pre-disaster and in-disaster phases.First,calculate the line failure probability based on typhoon weather forecast information from the previous day,and generate a probabilistic failure scenario set under typhoon conditions.Then,a"pre-disaster and in-disaster coordinated scheduling"model for distribution networks is established.The pre-disaster preventive scheduling model aims to maximize the expected load supply under various failure scenarios,optimizing the pre-deployment of emergency power vehicles and the operation mode of the distribution network.The in-disaster real-time response model aims to maximize load supply under real-time failures during the typhoon,adjusting the pre-deployment of emergency power vehicles.For model solving,considering the need for rapid intraday solutions,the soft actor-critic(SAC)reinforcement learning algorithm is employed to solve the in-disaster real-time response model.To enhance convergence,the Bayesian optimization algorithm is introduced to optimize the hyperparameters of the SAC algorithm,and a meta-learning mechanism is embedded to quickly address new sudden failures during typhoons.Finally,case study results demonstrate that the proposed method offers significant advantages in load supply and scheduling efficiency,effectively improving the emergency response capability of distribution networks under typhoon disasters.