Method to decide a multi-fault rush repair robust strategy in power distribution networks

摘要

The multi-fault rush repair problem (MRRP) in power distribution networks is a discrete dynamic combinatorial problem with topology constraints and a series of uncertain factors in repairing process. This paper aims to obtain a robust repairing strategy by studying the uncertainty of fault repairing time in order to minimize the outage loss and total repairing time. To solve the above problem, sensitive faults will be considered to obtain the robust repairing. The robust repairing time model is proposed based on timed Petri Net model with inhibitor arcs, which is adopted to analyze the repairing process to obtain the impact factor of every fault in a power distribution network. To simulate the uncertainties of repairing process, a Latin hypercube sampling method combined with the simultaneous backward reduction algorithm is used to generate simulation scenarios. The continuous bacterial colony chemotaxis (BCC) optimization algorithm is revised to be applicable for integer variables so as to find the optimal solution of each scenario in MRRP. Then the improved minimax regret criterion is applied to decide the final optimal robust repairing strategy. This approach is verified by the standard IEEE 33-bus system and a real-world power distribution network. Scenarios with deterministic and uncertain repairing time are discussed and the simulation results show the robustness and effectiveness of the approach.