摘要
结合粒子群算法与模拟退火算法各自的优点,文章提出一种基于模拟退火的粒子群优化算法。基于全局优化的思想,以中央空调系统总能耗的最低为优化目标,将各设备运行参数的变化范围以及设备之间的热交换作为约束条件,建立中央空调系统的全局优化模型。运用基于模拟退火的粒子群算法对空调系统运行参数进行动态优化,确定最佳工况点,仿真结果表明,优化之后的系统节能效果明显。
Combining the advantages of the particle swarm algorithm and the simulated annealing algorithm,this paper proposes a particle swarm optimization algorithm based on simulated annealing.Guided by the idea of global optimization,the minimum total energy consumption of a central air conditioning system is taken as the optimization objective,and the variation range of operating parameters and the heat exchange between devices are used as the constraints.Then,a global optimization model for the central air conditioning system is built.The particle swarm optimization algorithm based on simulated annealing is employed to dynamically optimize the operation parameters of the air conditioning system,and the optimal operating point is determined.The simulation indicates that the energy-saving effect of the optimized system is significant.
作者
曾建
杨祥国
刘自然
荣晨光
ZENG Jian;YANG Xiangguo;LIU Ziran;RONG Chenguang
出处
《中国修船》
2022年第3期34-38,共5页
China Shiprepair
基金
湖北省自然科学基金项目(2017CFB726)。
关键词
船舶中央空调系统
模拟退火算法
粒子群算法
能耗优化
central air conditioning system on ships
simulated annealing algorithm
particle swarm algorithm
energy consumption optimization
