【摘要】 建立高效的输电线路应急抢修物资调度模型及算法对快速修复电力系统故障具有重要意义。提出了有运输能力约束的时间和费用最优的应急资源调度模型，并基于模型建立适应度函数。同时，使用混合粒子群遗传算法(PSO-GA)对经典遗传算法进行改进，计算求得最优调度解。仿真实验表明，与遗传算法相比，PSO-GA算法收敛速度更快，且能找到更优秀的解群。通过建立的模型算法获得的最优调度方案优于由遗传算法获得的调度方案，所用时间和费用较少，平均减少大约10%,效果较好。更多还原

【Abstract】 Establishing an efficient dispatch model and algorithm of emergency repair supplies for transmission lines is of great significance to the rapid repair of power system faults. This paper proposes an emergency supplies dispatch model with transportation capacity constraints that is optimal in time and cost, and establishes a fitness function based on the model. At the same time, particle swarm optimization-genetic algorithm(PSO-GA) improves the classical genetic algorithm and calculates the optimal dispatch solution. Through a large number of simulation experiments, compared with genetic algorithm, PSO-GA algorithm converges faster and can find better solution groups. The optimal dispatch scheme obtained by the model algorithm is better than the dispatch scheme obtained by the genetic algorithm. The time and cost are less, and the average reduction is about 10%. The effect is better.更多还原