摘要
针对现有带式输送机运行方式能耗和电费开支较高的情况,以及节能优化策略考虑因素较为单一的问题,提出了将分时电价作为约束条件,利用遗传算法对能耗和电费开支进行全局优化,从而找到不同电价时段的最佳煤流量和运行速度,并对比了不同运行方式下的能耗和电费开支。结果表明:采用智能遗传算法优化运输策略能够降低40%以上的能耗和用电成本,具有一定的社会和经济效益。
In view of the high energy consumption and electricity cost of the existing belt conveyors and the single factor considered in the optimization strategy of energy saving,the time-sharing electricity price is put forward as the constraint condition.Genetic algorithm is used to optimize the energy consumption and electricity cost,so as to find out the best coal flow rate and running speed in different electricity price periods,and compare the energy consumption and electricity cost under different operation modes.The results show that the intelligent genetic algorithm can reduce the energy consumption and electricity cost by more than 40%,which has important social and economic benefits.
作者
李洋
LI Yang(Xishan Coal and Electricity Group Malan Multi-Business Branch,Gujiao 030205,China)
出处
《机械工程与自动化》
2019年第2期71-73,共3页
Mechanical Engineering & Automation
关键词
带式输送机
节能优化策略
遗传算法
全局优化
belt conveyor
energy-saving optimization strategy
genetic algorithm
global optimization
