Ayman Al Zawaideh;Khalifa Al Hosani;Igor Boiko;Mohammad Luai Hammadih
{"title":"并联压缩机的最小能量自适应负载分配","authors":"Ayman Al Zawaideh;Khalifa Al Hosani;Igor Boiko;Mohammad Luai Hammadih","doi":"10.1109/OJIA.2022.3192565","DOIUrl":null,"url":null,"abstract":"Compressors operating in parallel are widely used in compressor stations on natural gas pipelines to address the required flow demands. This paper presents a design of a new control structure and a load sharing optimal adaptive controller for multiple compressors connected in parallel and equipped with variable speed drives. The load sharing optimization (LSO) controller computes the split factor to distribute the flow among the compressors which depends on the current operating conditions, with the optimization's objective being to minimize the total energy consumption. In addition, the compressor maps are continuously updated to account for any changes due to external and untraceable factors resulting in an enhancement of the LSO. The presented control structure includes a common single controller for parallel compressors, which eliminates the need for loop-decoupling. Thus, ensuring a better stability and a faster dynamics with respect to the flow or pressure process variable. The proposed control structure and the adaptive LSO performance is evaluated through simulations and a lab hardware setup. The results show an improvement of more than 4% in the total energy consumption compared to an equal load sharing scheme and more than 2.5% compared to the equal distance to surge industrial scheme. This efficiency improvement leads to significant energy cost saving over large periods of time.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"3 ","pages":"178-191"},"PeriodicalIF":7.9000,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8782707/9666452/09834116.pdf","citationCount":"0","resultStr":"{\"title\":\"Minimum Energy Adaptive Load Sharing of Parallel Operated Compressors\",\"authors\":\"Ayman Al Zawaideh;Khalifa Al Hosani;Igor Boiko;Mohammad Luai Hammadih\",\"doi\":\"10.1109/OJIA.2022.3192565\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Compressors operating in parallel are widely used in compressor stations on natural gas pipelines to address the required flow demands. This paper presents a design of a new control structure and a load sharing optimal adaptive controller for multiple compressors connected in parallel and equipped with variable speed drives. The load sharing optimization (LSO) controller computes the split factor to distribute the flow among the compressors which depends on the current operating conditions, with the optimization's objective being to minimize the total energy consumption. In addition, the compressor maps are continuously updated to account for any changes due to external and untraceable factors resulting in an enhancement of the LSO. The presented control structure includes a common single controller for parallel compressors, which eliminates the need for loop-decoupling. Thus, ensuring a better stability and a faster dynamics with respect to the flow or pressure process variable. The proposed control structure and the adaptive LSO performance is evaluated through simulations and a lab hardware setup. The results show an improvement of more than 4% in the total energy consumption compared to an equal load sharing scheme and more than 2.5% compared to the equal distance to surge industrial scheme. This efficiency improvement leads to significant energy cost saving over large periods of time.\",\"PeriodicalId\":100629,\"journal\":{\"name\":\"IEEE Open Journal of Industry Applications\",\"volume\":\"3 \",\"pages\":\"178-191\"},\"PeriodicalIF\":7.9000,\"publicationDate\":\"2022-07-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/iel7/8782707/9666452/09834116.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Open Journal of Industry Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/9834116/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Open Journal of Industry Applications","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/9834116/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Minimum Energy Adaptive Load Sharing of Parallel Operated Compressors
Compressors operating in parallel are widely used in compressor stations on natural gas pipelines to address the required flow demands. This paper presents a design of a new control structure and a load sharing optimal adaptive controller for multiple compressors connected in parallel and equipped with variable speed drives. The load sharing optimization (LSO) controller computes the split factor to distribute the flow among the compressors which depends on the current operating conditions, with the optimization's objective being to minimize the total energy consumption. In addition, the compressor maps are continuously updated to account for any changes due to external and untraceable factors resulting in an enhancement of the LSO. The presented control structure includes a common single controller for parallel compressors, which eliminates the need for loop-decoupling. Thus, ensuring a better stability and a faster dynamics with respect to the flow or pressure process variable. The proposed control structure and the adaptive LSO performance is evaluated through simulations and a lab hardware setup. The results show an improvement of more than 4% in the total energy consumption compared to an equal load sharing scheme and more than 2.5% compared to the equal distance to surge industrial scheme. This efficiency improvement leads to significant energy cost saving over large periods of time.