Enhancing Resilience Level of Power Distribution Systems Using Proactive Operational Actions

Abstract

Growing widespread outages in power systems caused by natural disasters have highlighted the necessity of applying defensive approaches with the goal of prompt service restoration. In this context, this paper proposes a stochastic model with the goal of optimally using proactive operational actions before the upcoming disturbance hits. The actions considered in this study include network reconfiguration and crew prepositioning. To take the effective actions, the model simulates probable damages caused by the events via a set of scenarios generated by Monte Carlo simulation method. The proposed model aims at minimizing the expected load curtailment caused by the event over the scenarios. To calculate the amount of load curtailments, potential post-disturbance actions are also considered in the model. The model is mathematically formulated in mixed integer linear programming (MILP) fashion which can be easily solved via available software packages. A standard distribution system with a realistic set of data is employed to validate the effectiveness of the proposed model.