{"title":"考虑通信中的多重不确定性的配电网中的协同电压控制","authors":"Ting Yang, Yachuang Liu, Hao Li, Yanhong Chen, Haibo Pen","doi":"10.1016/j.segan.2024.101459","DOIUrl":null,"url":null,"abstract":"<div><p>Delays, jitter, and packet loss in communication networks can impact the performance of cooperative voltage control systems in distribution networks. In distribution systems with a high penetration of renewable energy sources that do not respond promptly, these issues can even lead to system destabilization when voltage surges occur. Considering the interdependence of delay, jitter, and packet loss, the current direct approach of accumulating information entropy may result in the deterioration of dynamic control performance. Based on Copula entropy theory, a new multivariate communication uncertainty metric model is proposed. Using the multivariate Epanechnikov kernel function model, a method has been developed to estimate the multivariate non-independent uncertainty of a communication system. Accurate state estimation is integrated into event-triggered sliding mode control (ETSMC) of the distribution network to facilitate coordinated voltage control and enhance resilience against communication uncertainty. Design criteria for the controller and observer parameters are provided based on Lyapunov stability theory. Simulation results confirm that the proposed ETSMC offers significant improvements in control performance and system resilience to external power disturbances and multivariate communication uncertainty events.</p></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":null,"pages":null},"PeriodicalIF":4.8000,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cooperative voltage control in distribution networks considering multiple uncertainties in communication\",\"authors\":\"Ting Yang, Yachuang Liu, Hao Li, Yanhong Chen, Haibo Pen\",\"doi\":\"10.1016/j.segan.2024.101459\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Delays, jitter, and packet loss in communication networks can impact the performance of cooperative voltage control systems in distribution networks. In distribution systems with a high penetration of renewable energy sources that do not respond promptly, these issues can even lead to system destabilization when voltage surges occur. Considering the interdependence of delay, jitter, and packet loss, the current direct approach of accumulating information entropy may result in the deterioration of dynamic control performance. Based on Copula entropy theory, a new multivariate communication uncertainty metric model is proposed. Using the multivariate Epanechnikov kernel function model, a method has been developed to estimate the multivariate non-independent uncertainty of a communication system. Accurate state estimation is integrated into event-triggered sliding mode control (ETSMC) of the distribution network to facilitate coordinated voltage control and enhance resilience against communication uncertainty. Design criteria for the controller and observer parameters are provided based on Lyapunov stability theory. Simulation results confirm that the proposed ETSMC offers significant improvements in control performance and system resilience to external power disturbances and multivariate communication uncertainty events.</p></div>\",\"PeriodicalId\":56142,\"journal\":{\"name\":\"Sustainable Energy Grids & Networks\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2024-07-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sustainable Energy Grids & Networks\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352467724001887\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Energy Grids & Networks","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352467724001887","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Cooperative voltage control in distribution networks considering multiple uncertainties in communication
Delays, jitter, and packet loss in communication networks can impact the performance of cooperative voltage control systems in distribution networks. In distribution systems with a high penetration of renewable energy sources that do not respond promptly, these issues can even lead to system destabilization when voltage surges occur. Considering the interdependence of delay, jitter, and packet loss, the current direct approach of accumulating information entropy may result in the deterioration of dynamic control performance. Based on Copula entropy theory, a new multivariate communication uncertainty metric model is proposed. Using the multivariate Epanechnikov kernel function model, a method has been developed to estimate the multivariate non-independent uncertainty of a communication system. Accurate state estimation is integrated into event-triggered sliding mode control (ETSMC) of the distribution network to facilitate coordinated voltage control and enhance resilience against communication uncertainty. Design criteria for the controller and observer parameters are provided based on Lyapunov stability theory. Simulation results confirm that the proposed ETSMC offers significant improvements in control performance and system resilience to external power disturbances and multivariate communication uncertainty events.
期刊介绍:
Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.