2024, Volume 26, Issue 2
Strategic Study of CAE >> 2024, Volume 26, Issue 2 doi: 10.15302/J-SSCAE-2024.07.011
Framework and Strategy for Enhancing Resilience of China’s Urban Power Systems under Extreme Natural Disasters
1. College of Interdisciplinary Studies, Hunan University of Technology and Business, Changsha 410205, China;
2. Xiangjiang Laboratory, Changsha 410205, China;
3. Changsha Social Laboratory of Artificial Intelligence,Hunan University of Technology and Business, Changsha 410205, China
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Abstract
The urban power system is a critical infrastructure that is essential for urban safety. The frequent occurrence of extreme natural disasters characterized by a low probability and high losses severely threatens the continuity of urban power supply and the overall safety of cities. Resilience is the capability of a system to withstand disturbances and rapidly return to normal operating conditions. Therefore, enhancing the resilience of urban power systems is crucial in the face of extreme natural disasters. This study provides an overview of the implications of enhancing resilience in urban power systems under extreme natural disasters, clarifying the processes by which urban power systems respond to extreme natural disasters. Subsequently, in conjunction with the challenges faced by the resilience construction of urban power systems under extreme natural disasters, key developmental elements for resilience improvement are analyzed from the information, physical, and application dimensions. Based on this, a framework for enhancing the resilience of urban power systems under extreme natural disasters is established. From the perspectives of data-driven sensing, scenario construction, response assessment, and emergency recovery, the framework dissects four critical technologies for improving the resilience of urban power systems. Furthermore, the following recommendations are proposed: (1) strengthening toplevel planning and coordinated design to upgrade power infrastructure through smart initiatives; (2) overcoming core issues and critical technologies and promoting the practical application of technological achievements; (3) enhancing standardized technical documents and establishing unified equipment configuration principles; and (4) advancing collaborative governance among diverse entities to establish an efficient emergency coordination mechanism.
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References
[ 1 ]
毕玮, 汤育春, 冒婷婷, 等. 城市基础设施系统韧性管理综述 [J]. 中国安全科学学报, 2021, 31(6): 14‒28.
Bi W, Tang Y C, Mao T T, et al. Review on resilience management of urban infrastructure system [J]. China Safety Science Journal, 2021, 31(6): 14‒28.
[ 2 ]
周姝天. 城市基础设施系统韧性提升策略初探 [J]. 城市与减灾, 2022, (5): 39‒43.
Zhou S T. Preliminary study on strategies to improve resilience of urban infrastructure system [J]. City and Disaster Reduction, 2022, (5): 39‒43.
[ 3 ] Homeland Security Blog Team. Presidential policy directive (PPD)-8 national preparedness [R]. Washington DC: U.S. Department of Homeland Security, 2011.
[ 4 ] European Commission. A framework strategy for a resilient energyunion with a forward-looking climate change policy [R]. Brussels: European Commission, 2015.
[ 5 ]
龚立, 王先培, 田猛, 等. 电力信息物理系统韧性的概念与提升策略研究进展 [J]. 电力系统保护与控制, 2023, 51(14): 169‒187.
Gong L, Wang X P, Tian M, et al. Concepts and research progress on enhancement strategies for cyber physical power system resilience [J]. Power System Protection and Control, 2023, 51(14): 169‒187.
[ 6 ]
郭伟, 安佳坤, 贺春光, 等. 计及冰灾影响的电力系统韧性评估与提升方法 [J]. 电力系统及其自动化学报, 2021, 33(8): 116‒122.
Guo W, An J K, He C G, et al. Resilience assessment and improvement method for power system considerinng the influences of ice disaster [J]. Proceedings of the CSU-EPSA, 2021, 33(8): 116‒122.
[ 7 ]
符杨, 顾吉平, 田书欣, 等. 基于地震灾害场景的主动配电网多维韧性评估方法 [J]. 电力自动化设备, 2023, 43(3): 1‒11.
Fu Y, Gu J P, Tian S X, et al. Multidimensional resilience evaluation method of active distribution network based on earthquake disaster scene [J]. Electric Power Automation Equipment, 2023, 43(3): 1‒11.
[ 8 ]
张鑫, 王楠, 王伟, 等. 考虑台风天气的电力系统韧性评估 [J]. 电力系统及其自动化学报, 2019, 31(8): 21‒26.
Zhang X, Wang N, Wang W, et al. Resilience assessment on power system under typhoon [J]. Proceedings of the CSU-EPSA, 2019, 31(8): 21‒26.
[ 9 ]
何秉顺. 河南郑州山区4市2021年"7·20"特大暴雨灾害调查的思考与建议 [J]. 中国防汛抗旱, 2022, 32(3): 37‒40, 51.
He B S. Thoughts and suggestions on the investigation of "July 20" torrential rain disaster in four cities in Zhengzhou Mountain Area of Henan Province in 2021 [J]. China Flood & Drought Management, 2022, 32(3): 37‒40, 51.
[10]
孙为民, 孙华东, 何剑, 等. 面向严重自然灾害的电力系统韧性评估技术综述 [J]. 电网技术, 2024, 48(1): 129‒139.
Sun W M, Sun H D, He J, et al. Review of power system resilience assessment techniques for severe natural disasters [J]. Power System Technology, 2024, 48(1): 129‒139.
[11]
别朝红, 林超凡, 李更丰, 等. 能源转型下弹性电力系统的发展与展望 [J]. 中国电机工程学报, 2020, 40(9): 2735‒2745.
Bie Z H, Lin C F, Li G F, et al. Development and prospect of resilient power system in the context of energy transition [J]. Proceedings of the CSEE, 2020, 40(9): 2735‒2745.
[12]
陈磊, 邓欣怡, 陈红坤, 等. 电力系统韧性评估与提升研究综述 [J]. 电力系统保护与控制, 2022, 50(13): 11‒22.
Chen L, Deng X Y, Chen H K, et al. Review of the assessment and improvement of power system resilience [J]. Power System Protection and Control, 2022, 50(13): 11‒22.
[13] Wender B A, Morgan M G, Holmes K J. Enhancing the resilience of electricity systems [J]. Engineering, 2017, 3(5): 580‒582.
[14] National Academies of Sciences, Engineering and Medicine, Division on Engineering and Physical Sciences, Board on Energy and Environmental Systems, etc. Enhancing the resilience of the nation´s electricity system [M]. Washington D C: National Academies Press, 2017.
[15] Mishra D K, Eskandari M, Abbasi M H, et al. A detailed review of power system resilience enhancement pillars [J]. Electric Power Systems Research, 2024, 230: 110223.
[16] Fulli G.Electricity security: Models and methods for supporting the policy decision making in the European union [D].Turin: Polytechnic University of Turin (Doctoral dissertation), 2016.
[17] Marnay C, Aki H, Hirose K, et al. Japan´s pivot to resilience: How two microgrids fared after the 2011 earthquake [J]. IEEE Power and Energy Magazine, 2015, 13(3): 44‒57.
[18]
尹积军, 夏清. 能源互联网形态下多元融合高弹性电网的概念设计与探索 [J]. 中国电机工程学报, 2021, 41(2): 486‒497.
Yin J J, Xia Q. Conceptual design and exploration of multi-factor integrated high-elastic power grid in energy Internet [J]. Proceedings of the CSEE, 2021, 41(2): 486‒497.
[19]
阮前途, 梅生伟, 黄兴德, 等. 低碳城市电网韧性提升挑战与展望 [J]. 中国电机工程学报, 2022, 42(8): 2819‒2830.
Ruan Q T, Mei S W, Huang X D, et al. Challenges and research prospects of resilience enhancement of low-carbon power grid [J]. Proceedings of the CSEE, 2022, 42(8): 2819‒2830.
[20]
程鑫, 樊扬, 龚贤夫, 等. 城市抗冰保底电网防灾综合评价指标体系研究 [J]. 电网技术, 2019, 43(10): 3808‒3815.
Cheng X, Fan Y, Gong X F, et al. Study on comprehensive evaluation index system for disaster prevention of urban ice-resistant secure power grid [J]. Power System Technology, 2019, 43(10): 3808‒3815.
[21] Zhou S C, Li Y F, Jiang C W, et al. Enhancing the resilience of the power system to accommodate the construction of the new power system: Key technologies and challenges [J]. Frontiers in Energy Research, 2023, 11: 1256850.
[22] Holling C S. Resilience and stability of ecological systems [J]. Annual Review of Ecology and Systematics, 1973, 4: 1‒23.
[23] Arghandeh R, von Meier A, Mehrmanesh L, et al. On the definition of cyber-physical resilience in power systems [J]. Renewable and Sustainable Energy Reviews, 2016, 58: 1060‒1069.
[24]
梁双, 严超, 厉瑜, 等. 电力系统应对极端天气自然灾害存在的薄弱环节及对策建议 [J]. 中国工程咨询, 2022 (9): 27‒31.
Liang S, Yan C, Li Y, et al. Weak links and countermeasures of power system in dealing with extreme weather and natural disasters [J]. China Engineering Consultants, 2022 (9): 27‒31.
[25]
康重庆, 姚良忠. 高比例可再生能源电力系统的关键科学问题与理论研究框架 [J]. 电力系统自动化, 2017, 41(9): 2‒11.
Kang C Q, Yao L Z. Key scientific issues and theoretical research framework for power systems with high proportion of renewable energy [J]. Automation of Electric Power Systems, 2017, 41(9): 2‒11.
[26]
何维国, 王赛一, 许唐云, 等. 城市韧性配电网建设与发展路径 [J]. 电网技术, 2022, 46(2): 680‒690.
He W G, Wang S Y, Xu T Y, et al. Construction and development path of the urban resilient distribution network [J]. Power System Technology, 2022, 46(2): 680‒690.
[27]
汤广福, 周静, 庞辉, 等. 能源安全格局下新型电力系统发展战略框架 [J]. 中国工程科学, 2023, 25(2): 79‒88.
Tang G F, Zhou J, Pang H, et al. Strategic framework for new electric power system development under the energy security pattern [J]. Strategic Study of CAE, 2023, 25(2): 79‒88.
[28]
石文辉, 屈姬贤, 罗魁, 等. 高比例新能源并网与运行发展研究 [J]. 中国工程科学, 2022, 24(6): 52‒63.
Shi W H, Qu J X, Luo K, et al. Grid-integration and operation of high-proportioned new energy [J]. Strategic Study of CAE, 2022, 24(6): 52‒63.
[29]
舒印彪, 陈国平, 贺静波, 等. 构建以新能源为主体的新型电力系统框架研究 [J]. 中国工程科学, 2021, 23(6): 61‒69.
Shu Y B, Chen G P, He J B, et al. Building a new electric power system based on new energy sources [J]. Strategic Study of CAE, 2021, 23(6): 61‒69.
[30]
刘瑞环, 陈晨, 刘菲, 等. 极端自然灾害下考虑信息-物理耦合的电力系统弹性提升策略: 技术分析与研究展望 [J]. 电机与控制学报, 2022, 26(1): 9‒23.
Liu R H, Chen C, Liu F, et al. Power system resilience enhancement strategy considering cyber-physical interdependence under disasters: Development and prospects [J]. Electric Machines and Control, 2022, 26(1): 9‒23.
[31]
秦潘昊, 陈威宇, 胡秦然, 等.新型电力系统设备状态监测与故障诊断传感芯片关键技术与展望 [J].电力系统自动化, 2024, 48(6): 83‒95.
Qin P H, Chen W Y, Hu Q R, et al. Key technologies and prospects of equipment condition monitoring and diagnostic sensor chips for new power systems [J]. Power System Automation, 2024, 48(6): 83‒95.
[32] Zhang W X, Shao C Z, Hu B, et al. Transmission defense hardening against typhoon disasters under decision-dependent uncertainty [J]. IEEE Transactions on Power Systems, 2023, 38(3): 2653‒2665.
[33]
盛戈皞, 钱勇, 罗林根, 等. 面向新型电力系统的数字化电力设备关键技术及其发展趋势 [J]. 高电压技术, 2023, 49(5): 1765‒1778.
Sheng G H, Qian Y, Luo L G, et al. Key technologies and development trends of digital power equipment for new type power system [J]. High Voltage Engineering, 2023, 49(5): 1765‒1778.
[34]
赵洪山, 孙京杰, 刘秉聪. 基于压缩感知的电力设备红外图像非盲自适应超分辨率方法 [J]. 高电压技术, 2022, 48(8): 3068‒3077.
Zhao H S, Sun J J, Liu B C. Non-blind adaptive super resolution method for infrared image of power equipment based on compressed sensing [J]. High Voltage Engineering, 2022, 48(8): 3068‒3077.
[35] Jia Y W, Meng K, Xu Z. N-k induced cascading contingency screening [J]. IEEE Transactions on Power Systems, 2015, 30(5): 2824‒2825.
[36]
李雪, 孙霆锴, 侯恺, 等. 极端天气下电力系统大范围随机设备故障的N-k安全分析及筛选方法 [J]. 中国电机工程学报, 2020, 40(16): 5113‒5126.
Li X, Sun T K, Hou K, et al. N-k security assessment and screening for large-scale random equipment faults in bulk power grid under extreme weather [J]. Proceedings of the CSEE, 2020, 40(16): 5113‒5126.
[37] Li G F, Huang G C, Bie Z H, et al. Component importance assessment of power systems for improving resilience under wind storms [J]. Journal of Modern Power Systems and Clean Energy, 2019, 7(4): 676‒687.
[38]
周姝天, 翟国方, 施益军, 等. 城市自然灾害风险评估研究综述 [J]. 灾害学, 2020, 35(4): 180‒186.
Zhou S T, Zhai G F, Shi Y J, et al. A literature review of urban natural disaster risk assessment [J]. Journal of Catastrophology, 2020, 35(4): 180‒186.
[39] Espinoza S, Panteli M, Mancarella P, et al. Multi-phase assessment and adaptation of power systems resilience to natural hazards [J]. Electric Power Systems Research, 2016, 136: 352‒361.
[40]
郄子君, 荣莉莉. 面向灾害情景推演的区域模型构建方法研究 [J]. 管理评论, 2020, 32(10): 276‒292.
Qie Z J, Rong L L. A construction method of hazard-affected region for disaster scenario evolution [J]. Management Review, 2020, 32(10): 276‒292.
[41]
刘翔宇, 李晓明, 朱介北, 等. 新型电力系统的频率响应模型综述及展望 [J]. 南方电网技术, 2022, 16(10): 38‒47.
Liu X Y, Li X M, Zhu J B, et al. Review and prospect on frequency response models of new power system [J]. Southern Power System Technology, 2022, 16(10): 38‒47.
[42] Morales-España G, Martínez-Gordón R, Sijm J. Classifying and modelling demand response in power systems [J]. Energy, 2022, 242: 122544.
[43] Vaish R, Dwivedi U D, Tewari S, et al. Machine learning applications in power system fault diagnosis: Research advancements and perspectives [J]. Engineering Applications of Artificial Intelligence, 2021, 106: 104504.
[44] Ajagekar A, You F Q. Quantum computing based hybrid deep learning for fault diagnosis in electrical power systems [J]. Applied Energy, 2021, 303: 117628.
[45] Zhang H T, Sun X F, Lee M H, et al. Deep reinforcement learning-based active network management and emergency load-shedding control for power systems [J]. IEEE Transactions on Smart Grid, 2024, 15(2): 1423‒1437.
[46]
杨挺, 耿毅男, 郭经红, 等. 人工智能在新型电力系统智能传感、通信与数据处理领域应用 [J]. 高电压技术, 2024, 50(1): 19‒29.
Yang T, Geng Y N, Guo J H, et al. Applications of artificial intelligence in sensing, communication, and data processing in the new power system [J]. High Voltage Engineering, 2024, 50(1): 19‒29.
[47] Li X, Du X X, Jiang T, et al. Coordinating multi-energy to improve urban integrated energy system resilience against extreme weather events [J]. Applied Energy, 2022, 309: 118455.
[48] Dobson I. Models, metrics, and their formulas for typical electric power system resilience events [J]. IEEE Transactions on Power Systems, 2023, 38(6): 5949‒5952.
[49] Panteli M, Mancarella P, Trakas D N, et al. Metrics and quantification of operational and infrastructure resilience in power systems [J]. IEEE Transactions on Power Systems, 2017, 32(6): 4732‒4742.
[50] Ganganath N, Wang J V, Xu X Z, et al. Agglomerative clustering-based network partitioning for parallel power system restoration [J]. IEEE Transactions on Industrial Informatics, 2018, 14(8): 3325‒3333.
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