Proactive allocation of mobile energy storage systems before a natural disaster to improve distribution system resilience

In the last few years, the vulnerability of distribution systems against extreme catastrophes has led electric companies to move towards resilient networks. Meanwhile, battery energy storage systems in distribution grids have been considered a promising solution due to their technical and economic advantages. This study proposes a proactive mobile energy storage optimal placement model (PMESOPM) to enhance the resilience of the power distribution system before a natural disaster. In this model, according to the fragility curve and probability of failure of components for lines and roads, Monte Carlo simulation is used to identify the failure states of any component in each iteration. Then, a pre-hurricane approach is adopted using the combination of genetic and Floyd algorithms to deploy mobile storage systems the day before the storm or hurricane. The numerical analysis is carried out using the IEEE 33-bus standard test network, mapped on the Sioux Falls traffic network. The results validate the effectiveness of the proposed model in critical conditions of the network.