| 引用本文: | 李妍莎,蔡 晔,曹一家,等.面向联合检修的电力信息物理系统输电线路脆弱相关性辨识[J].电力系统保护与控制,2022,50(24):120-128.[点击复制] |
| LI Yansha,CAI Ye,CAO Yijia,et al.Vulnerable correlation identification of a transmission line in the power cyber physicalsystem for federated maintenance[J].Power System Protection and Control,2022,50(24):120-128[点击复制] |
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| 摘要: |
| 为减少用户停电时间，电力企业常采取“一停多用，联合检修”模式。然而，检修计划往往侧重于关注线路本身的运行状态，而缺乏对电网整体运行性能的考虑。在跨区联合检修中，由于多条线路陆续停电检修，系统的脆弱性可能被放大。电力信息物理系统之间的融合关系也可能加剧故障跨域传播的深度和广度。在协同破坏效应下，系统存在连锁故障及大停电的可能。为此，提出一种该场景下输电线路脆弱相关性的辨识方法。首先，对联合检修中的能量流动和信息传输过程建模，构建联合检修事故记录数据库。其次，挖掘数据库中存在脆弱相关性的线路组合，通过计算线路组合在诱发停电事故时的贡献度，实现脆弱相关性的量化。仿真结果表明：联合检修时，脆弱相关的线路组在物理层和信息层都表现出了协同破坏效应。所提方法能有效地辨识和量化线路组的脆弱相关性，为制定更加合理的联合检修计划、避免大停电事故的发生提供理论指导。 |
| 关键词: 电力信息物理系统 联合检修 协同破坏 脆弱相关性辨识 |
| DOI：DOI: 10.19783/j.cnki.pspc.220229 |
| 投稿时间：2022-02-25修订日期：2022-03-22 |
| 基金项目:国家自然科学基金联合基金项目资助(U1966207)；湖南省自然科学基金项目资助(2020JJ5573，2020JJ5585) |
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| Vulnerable correlation identification of a transmission line in the power cyber physicalsystem for federated maintenance |
| LI Yansha,CAI Ye,CAO Yijia,LIU Fang,LI Long,TANG Xiafei |
| (1. School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410114, China;
2. Dispatching Control Center, State Grid Hunan Electric Power Co., Ltd., Changsha 410114, China)) |
| Abstract: |
| To reduce the outage time, federated maintenance with multiple lines outages is adopted by the power enterprise gradually. The line's condition is the focus, while the total operating status of the grid is ignored when making the maintenance decision. Multiple lines are out of operation successively, and this amplifies the system vulnerability. The interaction between the power cyber physical system (CPS) aggravates the cross-domain propagation of failure. There is the possibility of cascading failure and blackout due to the synergistic destructive effect. A method is proposed to identify the vulnerable correlation among the transmission lines in this scenario. First, the federated maintenance's energy flow and information transmission process are modeled. A database of accident records caused by the federated maintenance is established. Second, the combinations of lines with the vulnerable correlation in the database are mined. The vulnerability correlations are quantified by calculating the contributions to triggering the blackout. Simulation results show that the lines with vulnerable correlation express the synergistic destructive effect both in the physical and the cyber layers. The method proposed can identify and quantify the vulnerable correlations efficiently. It can provide the theoretical guidance for making reasonable maintenance decisions and avoiding blackouts.
This work is supported by the Union Funds of the National Natural Science Foundation of China (No. U1966207). |
| Key words: cyber physical system federated maintenance synergistic destructive effect identification of vulnerable correlation |
