Resilient-enhancing critical load restoration using mobile power sources with incomplete information

2021 
Abstract Mobile power sources (MPSs) have great potentials to enhance the resilience of distribution system due to mobility and flexibility. However, because of incomplete and asynchronous data after a natural disaster, decisions may lead to under-utilization of MPS and weak recovery performance. This paper proposes a robust receding horizon recovery strategy that dispatches MPSs and forms multiple microgrids (MGs) to maximize the restored critical loads (CLs). The receding horizon framework is utilized to update the system information dynamically and re-optimize the problem until accomplishment of the recovery process. A two-stage robust optimization formulation is adopted to take into account the problem uncertainty, i.e. unknown status of branches in damaged areas. Due to long-lasting duration of the recovery process, charging capability for re-chargeable MPSs is added to the proposed approach. Several case studies are carried out on IEEE 33-node distribution test system and IEEE 123-node test feeder to verify the effectiveness of proposed framework. The benefits of the new model are remarkable when there is a significant level of incomplete information, which is a likely case after high impact natural disasters.
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