A New Paradigm for Emergency Outage Scheduling in Industrial Parks: A Dynamic Scenario-Driven Multi-Period Optimization Strategy under Dual Uncertainty

Unplanned outage multi-time stochastic robust optimal scheduling strategy considering outage duration uncertainty. The uncertainty of external outage duration leads to the failure of the existing scheduling model to design a unified scheduling time window, and the uncertainty of internal renewable energy output affects the scheduling strategy of the system. Therefore, a multi-time scheduling strategy considering the uncertainty of outage duration is proposed in this paper. Firstly, the uncertainty of power outage duration is modeled and analyzed. The external uncertainty is described by probability distribution and scenario method, and the internal renewable energy output uncertainty is described by fluctuation interval. Secondly, aiming at minimizing the various costs of power failure loss in industrial parks, a multi-period stochastic robust scheduling framework based on scene method is proposed by designing power failure scenarios with different scheduling times. In each period, the model is solved by the Benders decomposition method and the scheduling instructions of the first period are executed. Finally, in the next period, the model is solved again according to the running state of the previous period and the updated blackout duration scenario and probability, and the scheduling decision during the complete blackout is obtained. A numerical example is used to verify that the proposed method may deal with the uncertainty caused by the unknown blackout duration and achieve the lowest expected outage losses.