Co-Optimization of Damage Assessment and Restoration: A Resilience-Driven Dynamic Crew Allocation for Power Distribution Systems
arXiv (Cornell University)(2023)
摘要
This study introduces a mixed-integer linear programming (MILP) model,
effectively co-optimizing patrolling, damage assessment, fault isolation,
repair, and load re-energization processes. The model is designed to solve a
vital operational conundrum: deciding between further network exploration to
obtain more comprehensive data or addressing the repair of already identified
faults. As information on the fault location and repair timelines becomes
available, the model allows for dynamic adaptation of crew dispatch decisions.
In addition, this study proposes a conservative power flow constraint set that
considers two network loading scenarios within the final network configuration.
This approach results in the determination of an upper and a lower bound for
node voltage levels and an upper bound for power line flows. To underscore the
practicality and scalability of the proposed model, we have demonstrated its
application using IEEE 123-node and 8500-node test systems, where it delivered
promising results.
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关键词
dynamic crew allocation,power distribution systems,damage assessment,co-optimization,resilience-driven
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