A Two-Stage Stochastic Programming Model for Proactive Scheduling of Distribution Networks with Emergency Resource Participation

Abstract

By implementing a proactive reserve scheduling mechanism, distribution networks (DNs) can optimize emergency resource deployment to improve fault recovery resilience. To address the limitations of existing pre-disaster preparation strategies that only consider limited resources, this paper proposes a proactive scheduling strategy that integrates mobile resources and field personnel in a coordinated manner for DNs. By establishing a two-stage stochastic mixed-integer programming (SMIP) model for coordinated control of emergency resources in DNs, the first stage determines the quantity and location of mobile energy storage systems (MESSs), repair crews (RCs), and switching crews (SCs). In the second stage, the emergency resources rapidly reach the affected sites to participate in sequential restoration of the DN. Finally, the model is validated using standard IEEE test systems. The results from the experiments demonstrate that the proposed method reduces load shedding cost by 19.0% and 19.9% on 33-node and 123-node systems. Empirical simulations confirm that the introduced framework enables efficient emergency resource orchestration, thereby enhancing the pre-disaster preventive response capability and post-disaster real-time restoration capability of the DN, significantly mitigating the impact of disruptive events.