基于关联规则的多冷水机组系统负荷优化分配

Optimal Load Allocation of Multiple Chiller System Based on Association Rules

本文以多冷水机组系统为研究对象,对系统采集的大量历史运行数据进行数据处理与分析,采用Apriori频繁项集算法,通过分级挖掘,挖掘在不同运行工况下各台冷水机组运行参数与最小运行能耗之间的关联规则,并以机组运行总能耗最小为目标,提出了一种将粒子群算法与关联规则结合的负荷分配优化方法。仿真验证结果表明:该方法通过优化冷水机组的启停和负荷率,可以有效减少机组运行的总能耗。与原有运行方式相比,实验日优化后多台冷水机组系统的总能耗降低约12.5%,具有良好的节能效果。

The aim of this study is to present an optimal method for load allocation in a multi-chiller system.By using the processed data from the historical operation data of the system,the Apriori frequent item set algorithm is used to mine the association rules among the operation variables and minimum energy consumption of each chiller under different operation conditions in stages.An optimal load allocation strategy combining a particle swarm optimization algorithm and association rules is proposed to minimize the total operation energy consumption of the chillers.The simulation results show that the optimal load allocation strategy can effectively reduce the total energy consumption of the chillers by optimizing the on-off and load ratio of the chiller.Compared with the original operation strategy,the total operation energy consumption of the system can be reduced by approximately 12.5%,and it is confirmed that the optimal load allocation strategy can save energy effectively.