全球能源互联网（英文）2024，Vol.7Issue(3)：336-346,11.DOI:10.1016/j.gloei.2024.06.005
极端灾害下提升电力数字孪生系统韧性的设备检修顺序优化决策方法
Optimal decision-making method for equipment maintenance to enhance the resilience of power digital twin system under extreme disaster
摘要
Abstract
Digital twins and the physical assets of electric power systems face the potential risk of data loss and monitoring failures owing to catastrophic events,causing surveillance and energy loss.This study aims to refine maintenance strategies for the monitoring of an electric power digital twin system post disasters.Initially,the research delineates the physical electric power system along with its digital counterpart and post-disaster restoration processes.Subsequently,it delves into communication and data processing mechanisms,specifically focusing on central data processing(CDP),communication routers(CRs),and phasor measurement units(PMUs),to re-establish an equipment recovery model based on these data transmission methodologies.Furthermore,it introduces a mathematical optimization model designed to enhance the digital twin system's post-disaster monitoring efficacy by employing the branch-and-bound method for its resolution.The efficacy of the proposed model was corroborated by analyzing an IEEE-14 system.The findings suggest that the proposed branch-and-bound algorithm significantly augments the observational capabilities of a power system with limited resources,thereby bolstering its stability and emergency response mechanisms.关键词
同步向量测量单元/贯序优化/韧性提升/通信网络/数字孪生Key words
Phasor measurement units/Through-sequence optimization/Resilience enhancement/Communication networks/Digital twins引用本文复制引用
高松,王伟,陈璟毅,吴欣昱,邵俊言..极端灾害下提升电力数字孪生系统韧性的设备检修顺序优化决策方法[J].全球能源互联网（英文）,2024,7(3):336-346,11.基金项目
This work was supported by the State Grid Jilin Province Electric Power Co,Ltd-Research and Application of Power Grid Resilience Assessment and Coordinated Emergency Technology of Supply and Network for the Development of New Power System in Alpine Region(Project Number is B32342210001). （Project Number is B32342210001）
