Pre-Disaster Allocation of Mobile Renewable-Powered Resilience-Delivery Sources in Power Distribution Networks

Unlike stationary wind turbines, mobile wind turbines (MWTs) can travel along the local transportation system (TS) via a truck, supplying power to microgrids (MGs), residential buildings, and critical infrastructure. This spatiotemporal flexibility can provide significant benefits, including enhancing system resilience in the aftermath of high-impact low-probability (HILP) incidents. However, the potential of such resources is currently untapped, calling for improved utilization. To address this research gap, this paper proposes an optimal scheme for strategically pre-positioning MWTs to enhance the resilience of MGs when facing extreme events. Considering that the MWTs travel time on the TS and the predicted wind energy have a significant impact on the duration and magnitude of power outages during the restoration process, a scenario-based stochastic mixed-integer linear programming (MILP) model is introduced to incorporate uncertainties related to the road status in the TS, power line faults in MGs, and wind energy forecasts. Case studies on an integrated transportation and energy network — a central Alabama interstate transportation network and two IEEE 33-node test power systems — demonstrate the effectiveness of the proposed pre-positioning scheme in boosting MGs resilience.