{"title":"分布式能源与多设备协调合作的分布式计算方法研究","authors":"Shiyuan Ning, Quanbo Ge, Haoyu Jiang","doi":"10.1109/YAC.2018.8406500","DOIUrl":null,"url":null,"abstract":"With the rapid development of the distributed renewable energy technologies, there is more significant increase in the amount of data generated by the smart grids, and there are a higher delay problem in the task processing, with the traditional centralized control methods, which brings in an adverse effect on the stable operation of the smart grid. Aiming at the problem, this paper proposes a distributed computing scheme that combines edge computing and cloud computing to improve power system data processing capabilities and system response capabilities. Besides, the paper analyzes the finiteness of edge node computing ability. According to the task load balancing theory, a task performance minimization as an objective function is proposed, and a high-performance load balancing strategy for immune chaotic particle swarms algorithm (ICPSO) is proposed based on this distributed computing architecture. Finally, the feasibility and effectiveness of the system architecture and load balancing strategy are verified through the simulation results.","PeriodicalId":226586,"journal":{"name":"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Research on distributed computing method for coordinated cooperation of distributed energy and multi-devices\",\"authors\":\"Shiyuan Ning, Quanbo Ge, Haoyu Jiang\",\"doi\":\"10.1109/YAC.2018.8406500\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the rapid development of the distributed renewable energy technologies, there is more significant increase in the amount of data generated by the smart grids, and there are a higher delay problem in the task processing, with the traditional centralized control methods, which brings in an adverse effect on the stable operation of the smart grid. Aiming at the problem, this paper proposes a distributed computing scheme that combines edge computing and cloud computing to improve power system data processing capabilities and system response capabilities. Besides, the paper analyzes the finiteness of edge node computing ability. According to the task load balancing theory, a task performance minimization as an objective function is proposed, and a high-performance load balancing strategy for immune chaotic particle swarms algorithm (ICPSO) is proposed based on this distributed computing architecture. Finally, the feasibility and effectiveness of the system architecture and load balancing strategy are verified through the simulation results.\",\"PeriodicalId\":226586,\"journal\":{\"name\":\"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/YAC.2018.8406500\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/YAC.2018.8406500","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on distributed computing method for coordinated cooperation of distributed energy and multi-devices
With the rapid development of the distributed renewable energy technologies, there is more significant increase in the amount of data generated by the smart grids, and there are a higher delay problem in the task processing, with the traditional centralized control methods, which brings in an adverse effect on the stable operation of the smart grid. Aiming at the problem, this paper proposes a distributed computing scheme that combines edge computing and cloud computing to improve power system data processing capabilities and system response capabilities. Besides, the paper analyzes the finiteness of edge node computing ability. According to the task load balancing theory, a task performance minimization as an objective function is proposed, and a high-performance load balancing strategy for immune chaotic particle swarms algorithm (ICPSO) is proposed based on this distributed computing architecture. Finally, the feasibility and effectiveness of the system architecture and load balancing strategy are verified through the simulation results.