{"title":"基于改进果蝇优化算法的冷冻水系统节能优化","authors":"Zengxi Feng, Wenjing Wang, Xin He, Gang Li, Lutong Zhang, Weipeng Xiang","doi":"10.1115/1.4062359","DOIUrl":null,"url":null,"abstract":"\n As the main energy consumption part of the central air-conditioning system, the energy saving of the chilled water system is particularly important. In this paper, an improved fruit fly optimization algorithm (IFOA) is used to optimize the operation parameters of the chilled water system to reduce the energy consumption of the chilled water system. In IFOA, the three-dimensional position coordinate is introduced to expand the search space of the algorithm, and the variable step strategy balances the global search ability and local search ability of the algorithm, and helps a single Drosophila jump out of the local optimization through chaos mapping. In order to verify the optimization effect of IFOA on the chilled water system, the energy consumption model of the chilled water system is established. With the lowest total energy consumption of the system as the goal, the operating parameters such as the chilled water supply temperature and the speed ratio of the chilled water pump are optimized. The simulation results show that the energy saving optimization method of central air-conditioning chilled water system based on IFOA can make the average energy saving rate of the system reach 7.9%. Compared with other optimization algorithms, the method has better energy saving effect and is more stable.","PeriodicalId":17404,"journal":{"name":"Journal of Thermal Science and Engineering Applications","volume":"26 1","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Energy saving optimization of chilled water system based on improved fruit fly optimization algorithm\",\"authors\":\"Zengxi Feng, Wenjing Wang, Xin He, Gang Li, Lutong Zhang, Weipeng Xiang\",\"doi\":\"10.1115/1.4062359\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n As the main energy consumption part of the central air-conditioning system, the energy saving of the chilled water system is particularly important. In this paper, an improved fruit fly optimization algorithm (IFOA) is used to optimize the operation parameters of the chilled water system to reduce the energy consumption of the chilled water system. In IFOA, the three-dimensional position coordinate is introduced to expand the search space of the algorithm, and the variable step strategy balances the global search ability and local search ability of the algorithm, and helps a single Drosophila jump out of the local optimization through chaos mapping. In order to verify the optimization effect of IFOA on the chilled water system, the energy consumption model of the chilled water system is established. With the lowest total energy consumption of the system as the goal, the operating parameters such as the chilled water supply temperature and the speed ratio of the chilled water pump are optimized. The simulation results show that the energy saving optimization method of central air-conditioning chilled water system based on IFOA can make the average energy saving rate of the system reach 7.9%. Compared with other optimization algorithms, the method has better energy saving effect and is more stable.\",\"PeriodicalId\":17404,\"journal\":{\"name\":\"Journal of Thermal Science and Engineering Applications\",\"volume\":\"26 1\",\"pages\":\"\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2023-04-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Thermal Science and Engineering Applications\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1115/1.4062359\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Thermal Science and Engineering Applications","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1115/1.4062359","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
Energy saving optimization of chilled water system based on improved fruit fly optimization algorithm
As the main energy consumption part of the central air-conditioning system, the energy saving of the chilled water system is particularly important. In this paper, an improved fruit fly optimization algorithm (IFOA) is used to optimize the operation parameters of the chilled water system to reduce the energy consumption of the chilled water system. In IFOA, the three-dimensional position coordinate is introduced to expand the search space of the algorithm, and the variable step strategy balances the global search ability and local search ability of the algorithm, and helps a single Drosophila jump out of the local optimization through chaos mapping. In order to verify the optimization effect of IFOA on the chilled water system, the energy consumption model of the chilled water system is established. With the lowest total energy consumption of the system as the goal, the operating parameters such as the chilled water supply temperature and the speed ratio of the chilled water pump are optimized. The simulation results show that the energy saving optimization method of central air-conditioning chilled water system based on IFOA can make the average energy saving rate of the system reach 7.9%. Compared with other optimization algorithms, the method has better energy saving effect and is more stable.
期刊介绍:
Applications in: Aerospace systems; Gas turbines; Biotechnology; Defense systems; Electronic and photonic equipment; Energy systems; Manufacturing; Refrigeration and air conditioning; Homeland security systems; Micro- and nanoscale devices; Petrochemical processing; Medical systems; Energy efficiency; Sustainability; Solar systems; Combustion systems