制冷技术2024，Vol.44Issue(1)：52-57,66,7.DOI:10.3969/j.issn.2095-4468.2024.01.203
应用深度学习和网格搜索的变频冷水机组节能优化策略研究
Research on Optimal Control Strategy of Chiller System Based on Deep Learning and Grid Search
摘要
Abstract
Chiller systems account for a huge energy consumption.To decoupling the variables of chillers with variable frequency compressor,pumps and fan,the paper uses deep neural networks to establish a multi-layer decoupling model.The real-time operating data of chillers from a factory in Ningbo in the past two years was collected as the training set and test set of the models.The prediction of chilled water return temperature,the frequency of cooling water pumps and chilled water pumps is achieved through environment variables and related control variables on the first stage.On this basis,the second stage we further establish a chiller power consumption prediction model.Finally,the optimal control parameters are determined by the grid search method.After testing,the average relative errors of the energy consumption prediction model are 4.61%.On a typical day,the energy consumption of the chiller under the optimized strategy operation was reduced by 9.96%.关键词
冷水机组/深度学习/优化控制Key words
Chiller/Deep learning/Optimized control分类
通用工业技术引用本文复制引用
韩林志,周镇新,方正辉,郑铁君,陈焕新..应用深度学习和网格搜索的变频冷水机组节能优化策略研究[J].制冷技术,2024,44(1):52-57,66,7.基金项目
国家自然科学基金(No.51876070). （No.51876070）
