A two-stage resilience improvement planning for power distribution systems against hurricanes

This paper presents a novel planning strategy for distribution system planners (DSPs) to enhance the resilience of distribution systems confronting emergencies. The problem is formulated as a two-stage stochastic programming model under emergency and normal scenarios. The decisions on line hardening, distributed generation (DG) placement, mobile emergency generators (MEG) allocation, and tie switch placement are made in the first stage to maximize the system resilience. In the second stage, the operation costs of the system pertaining to the DSP power purchase from the upstream network, DG power production, and forced load shedding in emergency conditions are minimized to achieve a techno-economic compromise of investment costs and enhanced operation/resilience benefits over both planning and operation scales. Since access to dependable distribution functions for probabilistic approaches is a notable challenge in resilience studies, an uncertainty modeling approach is presented based on the thresholds for the line damage in the worst-case event. The proposed approach can drastically decrease the number of line damage scenarios for resilience studies. The efficiency and effectiveness of the new approach are validated on two distribution system testbeds with 33 and 118 nodes.