Optimal decision-making method for equipment maintenance to enhance the resilience of power digital twin system under extreme disaster

• DOI: 10.1016/j.gloei.2024.06.005
• Publication Date: 2024-06-29T19:18:11Z
• Authors: Song Gao; Wei Wang; Jingyi Chen; Xinyu Wu; Junyan Shao
• Keywords: Communication networks; Through-sequence optimization; Phasor measurement units; 0211 other engineering and technologies; HD9502-9502.5; 02 engineering and technology; Energy conservation; Digital twins; Energy industries. Energy policy. Fuel trade; Resilience enhancement; TJ163.26-163.5

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.