{"title":"Towards Forming Optimal Communication Network for Effective Power System Restoration","authors":"Anna Volkova;Abdorasoul Ghasemi;Hermann de Meer","doi":"10.1109/TNSM.2024.3429204","DOIUrl":null,"url":null,"abstract":"Restoration of modern interdependent Information and Communication Technology (ICT) and power networks relies on preplanned and reactive strategies to consider simultaneous communication and power system recovery. This paper addresses the problem of finding and energizing a proper communication network connecting the distributed power grid assets in the restoration process, assuming a probability of infeasibility of recovering each communication node. The proper network has the minimum size, meets the communication requirements of power system recovery, and guarantees robustness against ICT nodes not being recoverable during restoration. The problem is formulated as a multi-objective optimization problem and solved using the genetic algorithm to find the optimal subgraph that ensures enough node-disjoint paths between the communicating power grid assets. Simulation results for the restoration strategy of the communication network associated with a power network are provided and discussed. The results show that networks’ ability to mitigate the adverse consequences of node failures can be significantly improved by incorporating just a few additional nodes and links while keeping the ICT network compact and feasible for restoration.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"21 5","pages":"5250-5259"},"PeriodicalIF":4.7000,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Network and Service Management","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10599521/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Restoration of modern interdependent Information and Communication Technology (ICT) and power networks relies on preplanned and reactive strategies to consider simultaneous communication and power system recovery. This paper addresses the problem of finding and energizing a proper communication network connecting the distributed power grid assets in the restoration process, assuming a probability of infeasibility of recovering each communication node. The proper network has the minimum size, meets the communication requirements of power system recovery, and guarantees robustness against ICT nodes not being recoverable during restoration. The problem is formulated as a multi-objective optimization problem and solved using the genetic algorithm to find the optimal subgraph that ensures enough node-disjoint paths between the communicating power grid assets. Simulation results for the restoration strategy of the communication network associated with a power network are provided and discussed. The results show that networks’ ability to mitigate the adverse consequences of node failures can be significantly improved by incorporating just a few additional nodes and links while keeping the ICT network compact and feasible for restoration.
期刊介绍:
IEEE Transactions on Network and Service Management will publish (online only) peerreviewed archival quality papers that advance the state-of-the-art and practical applications of network and service management. Theoretical research contributions (presenting new concepts and techniques) and applied contributions (reporting on experiences and experiments with actual systems) will be encouraged. These transactions will focus on the key technical issues related to: Management Models, Architectures and Frameworks; Service Provisioning, Reliability and Quality Assurance; Management Functions; Enabling Technologies; Information and Communication Models; Policies; Applications and Case Studies; Emerging Technologies and Standards.