{"title":"Research on Optimization of Chiller Based on Adaptive Weight Particle Swarm Algorithm","authors":"Anping Lu, Qiang Ding, Aipeng Jiang","doi":"10.1109/ICCAIS.2018.8570511","DOIUrl":null,"url":null,"abstract":"To study the parameters of minimum energy consumption and optimal performance of the system under specific load, the refrigeration mainframe of the cold water system is analyzed and selected, the performance model of the main engine and the pumps are built according to the actual situation. The load limitation of the constant frequency compressor is analyzed, the load ratio can be adjusted in a larger range by frequency conversion compressor, the adaptive weight particle swarm optimization algorithm is used to optimize the solution, and the comparison with the traditional constant flow scheme is made. The maximum energy saving is 11.25%, which shows the advantage of the intelligent algorithm.","PeriodicalId":223618,"journal":{"name":"2018 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Control, Automation and Information Sciences (ICCAIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCAIS.2018.8570511","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
To study the parameters of minimum energy consumption and optimal performance of the system under specific load, the refrigeration mainframe of the cold water system is analyzed and selected, the performance model of the main engine and the pumps are built according to the actual situation. The load limitation of the constant frequency compressor is analyzed, the load ratio can be adjusted in a larger range by frequency conversion compressor, the adaptive weight particle swarm optimization algorithm is used to optimize the solution, and the comparison with the traditional constant flow scheme is made. The maximum energy saving is 11.25%, which shows the advantage of the intelligent algorithm.