Optimal Scheduling of Distribution Network Maintenance Personnel Based on The Northern Goshawk Optimization Algorithm

Extreme events have caused large-scale power disruptions across the planet in recent years. Extreme events can cause multiple faults in the distribution network, maintenance personnel must be sent out to fix the faulty lines since the distribution network cannot be repaired in its entirety through islanding and reconfiguration. However, the number of faulty lines often exceeds the amount of the maintenance workforce, and there are also variations in the maintenance times of individual maintenance personnel. How to schedule maintenance personnel in a rational manner to minimize the total economic cost is the problem to be addressed in this study. Firstly, in order to model load uncertainty, Monte Carlo approach is utilized to model various scenarios. Secondly, the modified Northern Goshawk Optimization algorithm is used to solve the best scheduling scheme. Finally, the effectiveness of the proposed method is verified by concrete examples.