蚁群算法在应急电源管理系统中的应用

Application of ant colony optimization algorithm in emergency power management system

为响应国家创新驱动战略,促进消防系统的技术革新,提高消防系统电源管理的高效化和智能化水平,通过研究蚁群算法在应急电源管理系统中的应用,提出一种基于蚁群算法的动态电源管理方案,实现系统巡查路径的迭代优化;设计了用于应急照明设备的电源管理系统,采用主动巡查与周期性定时巡查结合的方式,实现应急电源分级控制、统筹分析的智能化管理,提高了系统的响应速率。基于Matlab平台设计了电源节点巡查的仿真对比实验,实验结果表明,采用蚁群算法的电源管理系统能够动态调整巡查节点、寻找最优巡查路径,有效缩短系统的巡查距离,提高系统的巡查效率和智能化程度。

In response to the national innovation⁃driven strategy,promoting the technical innovation of the fire protection system,and further improving the efficiency and intelligent level of the power management of fire protection system,the application of ant colony optimization(ACO)algorithm in the emergency power supply management system is studied to put forward a dynamic power management solution based on ACO algorithm,so as to realize the iterative optimization of the system search path.A power management system for emergency lighting equipment is designed.In this system,active inspection is combined with periodic and regular inspection to realize the emergency power intelligent management of hierarchical control and overall analysis,which improves the response rate of the system.The simulation and contrastive experiment of power node inspection was designed based on Matlab platform.The experimental results show that the power management system using ACO algorithm can dynamically adjust the inspection node,find out the optimal inspection path,effectively shorten the inspection distance of the system,and improve its inspection efficiency and intelligence level.