Dynamic Multi-Criteria Crew Dispatch For Power Distribution Fault Inspection

With the increasing frequency of natural disasters that cause damage to power systems, significant challenges arise in the detection, isolation, and restoration of faults. While the research community focuses on dispatching repair crews, less attention has been given to inspection crews, responsible for identifying the location and nature of faults. This paper proposes a dynamic bi-objective model for dispatching inspection crews, aiming to minimize routing efforts while prioritizing areas with higher fault probabilities. Posterior fault probabilities are estimated through Bayes’ theorem and updated dynamically as new faults are identified. The proposed framework also integrates a dynamic decision-making process, allowing weight adjustments whenever new routing is required. Results demonstrate that the model generates non-convex Pareto fronts, showing the advantage of multi-objective optimization techniques such as the ϵ-constraint method. Numerical experiments on the IEEE-34 test system demonstrate that dynamically adjusting decision weights leads to substantial improvements in fault detection time in the scenario considered.