Optimization of maintenance personnel dispatching strategy in smart grid

Efficient and timely dispatch of maintenance personnel for fault detection and failure recovery play a key role towards safe operation of power grid and has become a challenging issue. To address this challenge, this paper proposes a new optimal strategy, namely adaptive NSGAII (NSGAII/A), for dispatching maintenance personnel in the event of security risk that can improve manpower efficiency and maintain the security of power grid at a minimum cost. To solve this optimization problem, we firstly model the optimization objectives and constraints in the process of maintenance personnel scheduling. Secondly, we improve the legacy nondominated sorting genetic algorithm II (NSGAII) to combat its shortcomings in the calculation of congestion and the strategy of individual selection. On one hand, NSGAII/A takes the absolute value of the average congestion degree minus the standard deviation as the individual congestion degree, so as to reduce the impact of the congestion degree of individual optimization objectives. Furthermore, it can prevent the algorithm from converging too fast and causing the problem of local optimization. On the other hand, we adopt the elitist control strategy to replace the elitist retention strategy of NSGAII. The extensive experimental results demonstrate that NSGAII/A has advantages in terms of the average value of optimization objectives, the maintenance completion degree, and the distribution of non-dominated solution set in the process of population optimization.