基于关联规则算法的冷水机组运行性能优化

Chiller operation performance optimization using association rule algorithm

提出了一种优化冷水机组运行性能的关联规则数据挖掘方法。以广州某商场不同额定功率的冷水机组为研究对象,利用冷水机组历史运行数据,通过Apriori频繁项集算法分析了各种运行工况下的单台冷水机组最佳运行能效与各运行参数之间的关联规则,以指导冷水机组的节能优化运行。仿真结果表明:利用该运行参数优化方法,2台不同额定功率的冷水机组能耗与原运行方式相比,分别在夏季和冬季降低了5.53%和11.80%,节能效果显著,验证了算法的有效性。其关联规则具有代表性和实用性,能够挖掘冷水机组的节能潜力。该方法适用于已积累大量运行数据的冷水机组,为冷水机组的节能优化运行提供参考。

Proposes an association rule data mining method to optimize the performance of chillers. Taking the different rated power chiller system of a shopping mall in Guangzhou as a research object,based on the previous running data,analyses the association rules between the optimal operation energy efficiency and the running parameters of a single chiller under different operating conditions by Apriori frequent item set algorithm to guide the optimal operation of chiller system.The simulation results show that the energy consumption of the two different rated power chillers is 5.53%and11.80%lower than that of the original operation mode in summer and winter respectively,with a remarkable energy saving effect,and verifies the validity of the algorithm.The rules are representative and practical,and can improve the energy saving potential of the chiller.This method is suitable for chillers with accumulated large amount of running data, which can provide reference for the energy saving and optimal operation of chillers.