A Method Of Multi-fault Rush Repair Scheduling For Distribution Networks Based On Adaptability Measure

The distribution system has the characters of equipment diversity and structuralcomplexity. Once multi-faults occur under emergencies, the plan of rush repair madethrough the managers’experience usually lacks of qualitative and quantitative analysis,and is hard to achieve the best effect. Based on consulting related materials from homeand abroad, this paper aims at constructing a system for distribution networks rush repairscheduling to give the rush repair resources allocation scheme and the emergency repairplan quickly and researching a kind of new method for distribution network rush repairscheduling to decrease the society economic loss caused by the faults in distributionnetwork.First of all, after fully analyzing the feature of the rush repair resources and faults, therush repair capacity vector, the fault resource requirement vector and the rush repairresources allocation adaptability measure are proposed; an optimum model for rush repairresources allocation is built to research on the organization structure optimization inearlier stage of the rush repair.Then, the rush repair scheduling in combination of the multi-agent theory is studied.A two stage optimum model based on the target of optimizing the organization structureand minimizing the lost is set up to research on the optimizing of the rush repairscheduling under the multi-team cooperation. The realization method on multi-agent isdesigned, which can get the resources allocation scheme and rush repair plan foremergencies rapidly and modify it immediately on progress by setting a variety of agentsand using blackboard coordination mechanism.This paper used the improved discrete bacterial colony chemotaxis algorithm to solvethe problem in optimizing of intelligent agents of multi-agent system. On one hand thebacterial colony chemotaxis algorithm by introducing a discrete updating mechanismbased on the characteristic of the rush repair is improved, and on the other hand, theoverall evolution ability and convergence speed using a series of operators is alsoimproved. At last, the model and multi-agent method proposed are confirmed to be accuracyand effectiveness by case formulated.