Two-Stage Strategy for Enhancing the Resilience of Distribution Networks through active and reactive Power Coordinated Optimization under Extreme Disasters
Liu Jiaxin1,2, Qin Wenping1,2, Xing Yahong3, Wang Peng4, Wang Yukun1,2
1. Shanxi Key Lab of Power System Operation and Control Taiyuan University of Technology Taiyuan 030024 China 2. Key Laboratory of Cleaner Intelligent Control on Coal & Electricity, Ministry of Education Taiyuan 030024 China 3. Key Laboratory of Energy Economics and Power Grid Planning Economic and Technology Research Institute of State Grid Shanxi Electric Power Company Taiyuan 030002 China 4. School of Electrical and Electronic Engineering Nanyang Technological University Singapore 639798 Singapore
Abstract：Extreme weather including typhoons, earthquakes and torrential rain disrupt power systems through distinct mechanisms, yet all induce multi-point failures. While focusing on distribution line damage scenarios, the proposed methodology applies equally to other equipment failures. Typhoons represent a high-impact archetype—causing widespread blackouts and equipment destruction—serving as a representative disturbance. This research addresses post-disaster resilience enhancement for active distribution networks under extreme typhoon scenarios characterized by two conditions: complete disconnection of affected distribution lines and isolation from transmission grids due to substation failures. During such events, remote controll switches partition distribution systems into self-powered islanded microgrids, coordinating operational distributed energy resources to restore critical loads. Simultaneously, distribution networks face challenges from fluctuating load demands and renewable generation. Insufficient reactive power can trigger voltage instability or even cause islanded microgrids to collapse. Given higher R/X ratios in distribution networks compared to transmission systems, neglecting reactive power distribution exacerbates voltage drops at nodes, leading to voltage limit violations and additional load shedding. Furthermore, unified optimization across a single timescale fails to leverage the full potential of controllable devices networks due to their heterogeneous response speeds, yielding suboptimal strategies in active distribution. This study proposes a two-stage islanded microgrid partitioning strategy. This strategy coordinates active and reactive power optimization while dispatching multiple devices across temporal scales, dynamically partitioning distribution systems into self-powered microgrids to ensure continuous reliable power supply for critical loads, thereby enhancing post-outage resilience. As electromechanical devices, remote controll switches and capacitor banks should avoid frequent operations. Thus, these devices were optimized at long-term timescales (set to 1-hour intervals) to minimize unnecessary switching and prolong service life. In contrast, distributed energy resources and static var compensators enable continuous control and rapid response to power fluctuations. Consequently, they were optimized at short timescales (20-minute intervals) for real-time system state adjustments. This timescale differentiation balances system responsiveness against equipment durability, with adjustable intervals accommodating operational requirements across scenarios. In the first stage, renewable generation and load demand forecasts for the next time window informed long timescale optimization of remote controlled switches, capacitor banks, and energy storage charge/discharge strategies.The second stage leveraged updated high-accuracy forecasts and the first stage decisions to refine distributed resource outputs and static var compensator operations at short timescales, compensating for prediction errors from the first stage. The coupled two-stage mechanism enhanced extreme-scenario resilience through robust the first stage decisions while enabling real-time error mitigation in the second stage. A rolling-horizon optimization dynamically updated source-load forecasts, synchronously adjusting network topology and equipment outputs to maximize decision timeliness. Simulations on a modified IEEE 33-node system demonstrated that: (i) The two-stage optimization framework effectively addresses renewable generation and load demand uncertainty through long timescale and short timescale coordination. Compared to the first stage robust strategies, the second Stage real-time dispatch enhanced load restoration outcomes, validating the critical function of dynamic adjustment mechanisms in eliminating source-load uncertainty impacts.(ii) The coordinated optimization of active and reactive powers improved voltage profiles while enhancing load recovery, strengthening resilient distribution systems' post-disaster recovery capability and ensuring stable operation under extreme events. Versus conventional single-timescale optimization, this approach further increased load restoration by matching differentiated device response characteristics while maintaining system stability.
刘佳昕, 秦文萍, 邢亚虹, 王鹏, 王钰琨. 极端灾害下有功-无功协同优化的两阶段配电网韧性提升策略[J]. 电工技术学报, 0, (): 250774-.
Liu Jiaxin, Qin Wenping, Xing Yahong, Wang Peng, Wang Yukun. Two-Stage Strategy for Enhancing the Resilience of Distribution Networks through active and reactive Power Coordinated Optimization under Extreme Disasters. Transactions of China Electrotechnical Society, 0, (): 250774-.
[1] 童晓阳, 王晓茹. 乌克兰停电事件引起的网络攻击与电网信息安全防范思考[J]. 电力系统自动化, 2016, 40(07): 144-148. Tong Xiaoyang, Wang Xiaoru, Inference and Countermeasure Presuppostion of Network Attack in Incident on Ukrainian Power Grid[J]. Automation of Electric Power Systems, 2016, 40(07): 144-148. [2] Busby J, Baker K, Bazilian M, Cascading risks: Understanding the 2021 winter blackout in Texas[J]. Energy Research & Social Science, 2021, 77(1): 102-106. [3] 许寅, 和敬涵, 王颖, 等. 韧性背景下的配网故障恢复研究综述及展望[J]. 电工技术学报, 2019, 34(16): 3416-3429. Xu Ying, He Jinghan, Wang Ying.A Review on Distribution System Restoration for Resilience Enhancement[J]. Transactions of China Electrotechnical Society, 2019, 34(16): 3416-3429. [4] 肖娟霞,李勇,韩宇,等.计及台风时空特性和灵活性资源协同优化的配电网弹性提升策略[J].电工技术学报,2024,39(23):7430-7446. Xiao Juanxia, Li Yong, Han Yu, et al.Resilience Enhancement Strategy for Distribution Networks Considering the Spatiotemporal Characteristics of Typhoon and the Collaborative Optimization of Flexible Resources[J]. Transactions of China Electrotechnical Society, 2024, 39(23): 7430-7446. [5] Fan M, Zhang Z, Tian T.The Analysis of the Information Needed for the Planning of Active Distribution System[C]// Electricity Distribution (CIRED 2013), 22nd International Conference and Exhibition on. IET, Stockholm, Sweden: IET 2013. [6] 邢海军, 程浩忠, 张沈习, 等. 主动配电网规划研究综述[J]. 电网技术, 2015, 39(10): 2705-2711. Xing Haijun, Cheng Haozhong, Zhang Shenxi, et al.Review of Active Distribution Network Planning. Power System Technology[J]. Power System Technology, 2015, 39(10): 2705-2711. [7] Chen C, Wang J, Ton D, et al.Modernizing distribution system restoration to achieve grid resiliency against extreme weather events: An integrated solution[J]. Proceedings of the IEEE, 2017, 105(7): 1267-1288. [8] 邓荣楠,宋梦,高赐威,等.考虑用户负荷决策依赖特性的配电网灾后恢复方法对比分析[J].电工技术学报,2024,39(23):7447-7462. Deng Rongnan, Song Meng, Gao Ciwei, et al.Comparative Analysis of Distribution System Load Restoration Considering Decision-Dependent Behaviors of Customers[J]. Transactions of China Electrotechnical Society, 2024, 39(23): 7447-7462. [9] Shen F, López JC, Wu Q, et al.Distributed self-healing scheme for unbalanced electrical distribution systems based on alternating direction method of multipliers[J]. IEEE Transactions on Power Systems, 2020, 35(3): 2190-2199. [10] Ambia M.N., Meng K., Xiao W., et al. Nested formation approach for networked microgrid self-healing in islanded mode[J]. IEEE Transactions on Power Delivery, 2021, 36(1): 452-464. [11] 文娟,谭阳红,何怡刚,等.含分布式电源的复杂配电网多阶段故障恢复方法[J].电工技术学报,2018,33(14):3332-3341. Wen Juan, Tan Yanghong, He Yigang.Multi-Stage Service Restoration Method for Complex Distribution Networks with Distributed Generators[J]. Transactions of China Electrotechnical Society, 2018, 33(14): 3332-3341. [12] 王红君, 陈智晴, 赵辉, 等. 考虑风光荷不确定性的配电网故障恢复策略[J]. 电网技术, 2022, 46(11): 4356-4363. Wang Hongjun, Chen Zhiqing, Zhao Hui, et al.Reconstruction Strategies for Fault Recovery of Active Distribution Network With Distributed Generation Uncertainties[J]. Power System Technology, 2022, 46(11):4356-4363. [13] 汤一达, 吴志, 顾伟, 等. 主动配电网故障恢复的重构与孤岛划分统一模型[J]. 电网技术, 2020, 44(07): 2731-2740. Tang Yida, Wu Zhi, Gu Wei, et al.Research on Active Distribution Network Fault Recovery Strategy Based on Unified Model Considering Reconstruction and Island Partition[J]. Power System Technology, 2022, 46(5): 31-39. [14] 彭寒梅, 刘子威, 谭貌, 等. 面向弹性提升的主动配电网重构与元件修复协同方法[J]. 电力系统保护与控制, 2022, 50(17): 35-44. Peng Hanmei, Liu Ziwei, Tan Mao, et al.Collaborative method for an active distribution network reconfiguration and component repair for resilience improvement[J]. Power System Protection and Control, 2022, 50(17): 35-44. [15] 吴振华, 边晓燕, 周波, 等. 计及信息-能量耦合节点重要度的主动配电网灾后孤岛划分方法[J]. 电力自动化设备, 2023, 43(02): 74-81. Wu Zhenhua, Bian Xiaoyan, Zhou Bo, et al.Island partition method of active distribution network after disaster considering importance of information-energy coupling nodes[J]. Electric Power Automation Equipment, 2023, 43(2): 74-81. [16] 庞凯元, 王崇宇, 文福拴, 等. 主动配电网灵活孤岛划分与实时调度策略[J]. 电力系统自动化, 2022, 46(22): 13-24. Pang Kaiyuan, Wang Chongyu, Wen Fushuan, et al.Flexible Islanding Partition and Real-time Scheduling Strategy for Active Distribution Network[J]. Automation of Electric Power Systems, 2022, 46(22):13-24. [17] Zhang C, Xu Y, Dong Z, et al.Three-stage robust inverter-based voltage/var control for distribution networks with high-level PV[J]. IEEE Transactions on Smart Grid, 2019, 10(1): 782-793. [18] 景祥,秦文萍,逯瑞鹏,等.信息物理耦合环境中面向韧性全过程提升的配电网无功规划[J].电力系统自动化, 2025, 49(06):96-105. Jing Xiang, Qin Wenping, Lu Ruipeng, et al.Reactive power planning for resilience enhancement in a cyber-physical environment for distribution system[J]. Automation of Electric Power Systems, 2025, 49(06):96-105. [19] 寇凌峰, 吴鸣, 李洋, 等. 主动配电网分布式有功无功优化调控方法[J]. 中国电机工程学报, 2020, 40(06): 1856-1865. Kou Lingfeng, Wu Ming, Li Yang, et al.Optimization and Control Method of Distributed Active and Reactive Power in Active Distribution Network[J]. Proceedings of the CSEE, 2020, 40(6): 1856-1864. [20] 黄大为,王孝泉,于娜,等.计及光伏出力不确定性的配电网混合时间尺度无功/电压控制策略[J].电工技术学报,2022,37(17):4377-4389. Huang Dawei, Wang Xiaoquan, Yu Na.Hybrid Timescale Voltage/Var Control in Distribution Network Considering PV Power Uncertainty[J]. Transactions of China Electrotechnical Society, 2022, 37(17): 4377-4389. [21] 于惠钧,马凡烁,陈刚,等.基于改进灰狼优化算法的含光伏配电网动态无功优化[J].电气技术,2024,25(04):7-15+58. Yu Huijun, Ma Fanshuo, Chen Gang, et al. Dynamic reactive power optimization of photovoltaic distribution network based on improved gray wolf optimization algorithm[J]. Electrical Engineering, 2024, 25(04): 7-15+58. [22] Lin W, Zhu J, Yuan Y, et al.Robust optimization for island partition of distribution system considering load forecasting error[J]. IEEE Access, 2019, 7: 64247-64255. [23] 张剑,崔明建,何怡刚.结合数据驱动与物理模型的主动配电网双时间尺度电压协调优化控制[J].电工技术学报,2024,39(05):1327-1339. Zhang Jian, Cui Mingjian, He Yigang.Dual Timescales Coordinated and Optimal Voltages Control in Distribution Systems using Data-Driven and Physical Optimization[J]. Transactions of China Electrotechnical Society, 2024, 39(05): 1327-1339. [24] Xu Y, Dong Z, Zhang R, et al.Multi-Timescale Coordinated Voltage/Var Control of High Renewable-Penetrated Distribution Systems[J]. IEEE Transactions on Power Systems, 2017, 32(6): 4398-4408. [25] Gilani M A, Kazemi A,Ghasemi M.Distribution system resilience enhancement by microgrid formation considering distributed energy resources[J]. Energy, 2020, 191: 1-13. [26] 陈伯达, 林楷东, 苏洁莹, 等. 基于鲁棒规划的综合能源微网孤岛划分方法[J]. 电力系统自动化, 2020, 44(10): 32-40. Chen Boda, Lin Kaidong, Su Jieying, et al.Robust Planning Based Method for Integrated Energy Microgrid Island Partition[J]. Automation of Electric Power Systems, 2020, 44(10):32-40. [27] 王要强,李午祥,韩婧,等.极端天气下配电网韧性评估及提升研究综述[J].电力建设,2025,46(03):1-15. Wang Yaoqiang, Li Wuxiang, Han Jing, et al.Review of Evaluation and Improvement of Distribution Network Resilience Under Extreme Weather[J]. Electric Power Construction, 2025, 46(3): 1-15. [28] Ding T, Li F, Li X, et al.Interval radial power flow using extended DistFlow formulation and Krawczyk iteration method with sparse approximate inverse preconditioner[J]. IET Generation, Transmission and Distribution, 2015, 9: 1998-2006. [29] Lavorato M, Franco J F, Rider M J, et al.Imposing radiality constraints in distribution system optimization problems[J]. IEEE Transactions on Power Systems, 2012, 27(1): 172-180. [30] Ferreira R S, Borges C L T, Pereira M V F. A flexible mixed-integer linear programming approach to the AC optimal power flow in distribution systems[J]. IEEE Transactions on Power Systems, 2014, 29(5): 2447-2459. [31] Zeng B, Zhao L.Solving two-stage robust optimization problems using a column-and-constraint generation method[J]. Operations Research Letters, 2013, 41(5): 457-461. [32] Bertsimas D, Litvinov E, Sun X A, et al.Adaptive robust optimization for the security constrained unit commitment problem[J]. IEEE Transactions on Power Systems, 2013, 28(1): 52-63. [33] Baran M E, Wu F F.Network reconfiguration in distribution systems for loss reduction and load balancing[J]. IEEE Transactions on Power Delivery, 1989, 4(2): 1401-1407.
