摘要
针对电力传输网检修任务调度的智能化需求,提出一种基于改进多种群粒子群的检修任务调度模型。对此,本研究首先以平均检修工作时间、检修运行风险值作为目标构建目标调度函数;其次在对比粒子群算法的基础上,提出多种群粒子群算法,并针对粒子群算法容易陷入局部最优的问题,对惯性权重、学习因子和初始粒子群进行改进,同时融入细菌趋化行为对粒子群的位置进行更新;最后通过仿真编程的方式,采用上述的改进算法对目标函数进行求解,得到该方法无论是在种群多样性,还是在目标函数值和平均检修时间方面,改进算法都具有明显优势。
Aiming at the intelligent demand of power transmission network maintenance task scheduling,a maintenance task scheduling model based on improved multi swarm particle swarm optimization is proposed.To solve this problem,this study first constructs the objective scheduling function with the average maintenance working time and maintenance operation risk value as the objectives;secondly,based on the comparison of particle swarm optimization algorithm,a variety of particle swarm optimization algorithms are proposed,and the inertia weight,learning factor and initial particle swarm optimization are improved,and bacterial chemotaxis behavior pair is integrated into the algorithm Finally,through simulation programming,the improved algorithm is used to solve the objective function,which shows that the improved algorithm has obvious advantages in population diversity,objective function value and average maintenance time.
作者
陈剑
张洁华
赵悦莹
Chen Jian;Zhang Jiehua;Zhao Yueying(Skills training center of State Grid Jiangsu Electric Power Co.,Ltd.,Suzhou Jiangsu 215000)
出处
《现代科学仪器》
2020年第5期161-166,共6页
Modern Scientific Instruments
关键词
多种群粒子群
细菌趋化行为
电力传输网
任务检修
建模仿真
multi population particle swarm optimization
bacterial chemotaxis
power transmission network
task maintenance
simulation
