{"title":"A Structure-Based Voltage Stability Index in Distribution System Through Dimensional Reduction","authors":"Hongshen Zhang;Yongtao Zhang;Shibo He;Jiming Chen","doi":"10.1109/TII.2025.3528523","DOIUrl":null,"url":null,"abstract":"Voltage collapse is a critical form of system instability in power systems, occurring when power generation is unable to meet power demand, resulting in considerable socio-economic impacts. Current methodologies for studying voltage collapse primarily utilize simulation-based approaches. While informative, they offer little theoretical insights into the mechanism of this perplexing phenomenon due to their numerical nature. This article introduces a novel analytical framework in distribution system based on dimension reduction. By effectively mapping high-dimensional systems into simpler, lower dimensional equivalents, our framework is capable of mathematically solving system equations. This subsequently differentiates the critical factors from the less influential ones and proposes a novel voltage stability index. The voltage stability index is directly calculated by the structure-based weighted sum of power demands without monitoring data. This approach facilitates the identification of potential origins of system instability and highlights components that are particularly vulnerable, thereby enabling more targeted and effective measures for system reinforcement and risk mitigation. We rigorously test our framework on seven different distribution systems, demonstrating its efficacy and potential as a tool for enhancing grid stability. Our findings indicate that this novel approach can offer significant advantages in understanding and mitigating the risks of voltage collapse.","PeriodicalId":13301,"journal":{"name":"IEEE Transactions on Industrial Informatics","volume":"21 4","pages":"3406-3415"},"PeriodicalIF":9.9000,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Industrial Informatics","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10856677/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Voltage collapse is a critical form of system instability in power systems, occurring when power generation is unable to meet power demand, resulting in considerable socio-economic impacts. Current methodologies for studying voltage collapse primarily utilize simulation-based approaches. While informative, they offer little theoretical insights into the mechanism of this perplexing phenomenon due to their numerical nature. This article introduces a novel analytical framework in distribution system based on dimension reduction. By effectively mapping high-dimensional systems into simpler, lower dimensional equivalents, our framework is capable of mathematically solving system equations. This subsequently differentiates the critical factors from the less influential ones and proposes a novel voltage stability index. The voltage stability index is directly calculated by the structure-based weighted sum of power demands without monitoring data. This approach facilitates the identification of potential origins of system instability and highlights components that are particularly vulnerable, thereby enabling more targeted and effective measures for system reinforcement and risk mitigation. We rigorously test our framework on seven different distribution systems, demonstrating its efficacy and potential as a tool for enhancing grid stability. Our findings indicate that this novel approach can offer significant advantages in understanding and mitigating the risks of voltage collapse.
期刊介绍:
The IEEE Transactions on Industrial Informatics is a multidisciplinary journal dedicated to publishing technical papers that connect theory with practical applications of informatics in industrial settings. It focuses on the utilization of information in intelligent, distributed, and agile industrial automation and control systems. The scope includes topics such as knowledge-based and AI-enhanced automation, intelligent computer control systems, flexible and collaborative manufacturing, industrial informatics in software-defined vehicles and robotics, computer vision, industrial cyber-physical and industrial IoT systems, real-time and networked embedded systems, security in industrial processes, industrial communications, systems interoperability, and human-machine interaction.