Abstract：With the continuous promotion of low-carbon transformation of green energy, a high proportion of distributed power sources are connected to the power grid, and the traditional single-radiation network becomes a source-load interactive multi-source network. The system operation mode changes in a wide range, resulting in a huge challenge for the staged current protection based on single-source fault characteristics. Although the existing adaptive protection technology improves flexibility by adjusting the protection setting value in real time, its core depends on accurate system equivalent impedance identification. However, the traditional identification method has significant errors under complex conditions such as new energy output fluctuation, multi-source coupling and internal disturbance of the system. Especially when the load side interacts with the distributed power supply on the system side, the failure of traditional assumptions leads to a sharp decline in identification accuracy. Aiming at the above problems, this paper proposes an impedance identification method based on fluctuation characteristic analysis. By reconstructing the mathematical model, optimizing the algorithm framework and multi-scenario verification, the system solves the problem of protection adaptability of high-proportion new energy distribution network. Traditional impedance identification methods can be divided into two categories based on network information and local information. The former relies on global topological parameters and has defects such as complex calculation and difficulty in online application. Although the latter uses local measurement information, the least square method, covariance method and other algorithms increase the error due to ignoring the potential fluctuation component and coupling effect in the new energy disturbance scenario. This paper innovatively proposes to decompose the equivalent potential of the system into a superposition model of steady-state value and fluctuation value, which breaks through the limitations of traditional methods on the assumption of constant potential or single variable. By analyzing the dynamic correlation between the fluctuation component and the system impedance, the impedance identification equation considering the coupling of multi-source disturbances is established, and the improved forgetting factor algorithm is used to dynamically adjust the weight of historical data, which effectively suppresses the influence of the algorithm itself. In the scenario of system-side potential fluctuation of ± 0.2% and ± 0.4% and load-side impedance disturbance of ± 5%, the method in this paper stabilizes the resistance and reactance identification errors within 5% and 3% respectively through the potential steady-wave decoupling model, which is more than 50% lower than the traditional method. For the sudden change of system impedance, the maximum tracking error of resistance and reactance of the proposed algorithm is only 4.34% and 1.08%. Aiming at the two-way coupling problem caused by the penetration of distributed power supply on the load side, a test scenario with 2 600 kW load side photovoltaic is constructed. The traditional method leads to an error of more than 15% due to source-load coupling, while the phase decoupling strategy in this paper reduces the average error to 0.92%. When the load impedance fluctuation is 10%, the maximum error of the improved forgetting factor method is reduced from 50% to 14%, and the average error is less than 5%. Experiments show that the proposed method meets the national standard requirements in the scenarios of new energy fluctuation, topology change and multi-source coupling, and provides high-precision parameter support for adaptive protection.
邓邦, 贾科, 毕天姝, 陈星屹, 孔嘉靖. 基于波动特性解析的配电系统阻抗辨识方法[J]. 电工技术学报, 2026, 41(3): 938-948.
Deng Bang, Jia Ke, Bi Tianshu, Chen Xingyi, Kong Jiajing. Impedance Identification Method of Distribution System Based on Fluctuation Characteristic Analysis. Transactions of China Electrotechnical Society, 2026, 41(3): 938-948.
[1] 王守相, 尹孜阳, 赵倩宇. 考虑多供电层级耦合的中低压配电网分布式光伏承载力一体化精细评估方法[J]. 电工技术学报, 2025, 40(6): 1930-1944. Wang Shouxiang, Yin Ziyang, Zhao Qianyu.A precise distributed PV hosting capability evaluation method for MV and LV distribution network conside-ring the coupling of multiple power supply layers[J]. Transactions of China Electrotechnical Society, 2025, 40(6): 1930-1944. [2] 孔宇, 张恒旭, 施啸寒, 等. 基于多时间尺度分层协同的电力系统开放式推演框架[J]. 电工技术学报, 2025, 40(7): 2063-2077. Kong Yu, Zhang Hengxu, Shi Xiaohan, et al.Open evolution simulation framework for power system based on multi-time scale hierarchical coordination[J]. Transactions of China Electrotechnical Society, 2025, 40(7): 2063-2077. [3] 戴志辉, 牛宝仪, 李铁成, 等. 基于控保协同的三端混合直流输电系统线路保护[J]. 电工技术学报, 2025, 40(1): 108-121. Dai Zhihui, Niu Baoyi, Li Tiecheng, et al.Line protection method of three-terminal hybrid DC transmission system based on control and protection coordination[J]. Transactions of China Electrotech-nical Society, 2025, 40(1): 108-121. [4] 贾科, 李昱霖, 毕天姝, 等. 基于早期故障判别的直流并网系统主动保护[J]. 电工技术学报, 2025, 40(5): 1427-1439. Jia Ke, Li Yulin, Bi Tianshu, et al.Incipient fault identification based active protection of DC collection line[J]. Transactions of China Electrotechnical Society, 2025, 40(5): 1427-1439. [5] 李君, 何敏, 黄守道, 等. 基于相位差的小电阻接地有源配电网接地故障保护算法[J]. 电工技术学报, 2024, 39(23): 7418-7429. Li Jun, He Min, Huang Shoudao, et al.Grounding fault protection algorithm of small resistance earthing active distribution network based on phase difference[J]. Transactions of China Electrotechnical Society, 2024, 39(23): 7418-7429. [6] 武岳, 范开俊, 徐丙垠, 等. 配合防孤岛保护的配电网时限自适应重合闸方法[J]. 电力系统自动化, 2024, 48(3): 122-132. Wu Yue, Fan Kaijun, Xu Bingyin, et al.Time-limited adaptive reclosing method for distribution networks in coordination with anti-islanding protection[J]. Automation of Electric Power Systems, 2024, 48(3): 122-132. [7] 付正鑫, 卢继平, 乔梁, 等. 基于戴维南参数等值的电压稳定性分析[J]. 中国电力, 2014, 47(5): 44-47. Fu Zhengxin, Lu Jiping, Qiao Liang, et al.Voltage stability analysis based on thevenin equivalent parameters[J]. Electric Power, 2014, 47(5): 44-47. [8] Moghimi Haji M, Xu W.Online determination of external network models using synchronized phasor data[J]. IEEE Transactions on Smart Grid, 2018, 9(2): 635-643. [9] Abdi P, Hamedani-Golshan M E, Alhelou H H, et al. A PMU-based method for on-line Thévenin equivalent estimation[J]. IEEE Transactions on Power Systems, 2022, 37(4): 2796-2807. [10] Vu K, Begovic M M, Novosel D, et al.Use of local measurements to estimate voltage-stability margin[J]. IEEE Transactions on Power Systems, 1999, 14(3): 1029-1035. [11] Begovic M, Milosevic B, Novosel D.A novel method for voltage instability protection[C]//Proceedings of the 35th Annual Hawaii International Conference on System Sciences, Big Island, HI, USA, 2002: 802-811. [12] 闫常友, 刘建飞, 杨奇逊, 等. 基于平方根滤波的网络等值算法[J]. 继电器, 2006, 34(3): 41-46. Yan Changyou, Liu Jianfei, Yang Qixun, et al.Research on real-time equivalent based on square-root algorithm[J]. Relay, 2006, 34(3): 41-46. [13] 常鲜戎, 王建文, 崔赵俊. 基于戴维南等值模型的静稳极限在线监视[J]. 电测与仪表, 2015, 52(16): 11-16. Chang Xianrong, Wang Jianwen, Cui Zhaojun.Static stability limit online monitoring based on Thevenin equivalent model[J]. Electrical Measurement & Instrumentation, 2015, 52(16): 11-16. [14] Zhou Ning, Trudnowski D J, Pierre J W, et al.Electromechanical mode online estimation using regularized robust RLS methods[J]. IEEE Transactions on Power Systems, 2008, 23(4): 1670-1680. [15] 刘明松, 张伯明, 姚良忠, 等. 基于PMU和改进戴维南等值模型的电压稳定在线监视[J]. 电力系统自动化, 2009, 33(10): 6-10. Liu Mingsong, Zhang Boming, Yao Liangzhong, et al.On-line voltage stability monitoring based on PMU and improved thevenin equivalent model[J]. Automa-tion of Electric Power Systems, 2009, 33(10): 6-10. [16] Ojaghi M, Sudi Z, Faiz J.Implementation of full adaptive technique to optimal coordination of overcurrent relays[J]. IEEE Transactions on Power Delivery, 2013, 28(1): 235-244. [17] Shen Shaofei, Lin Da, Wang Huifang, et al.An adaptive protection scheme for distribution systems with DGs based on optimized thevenin equivalent parameters estimation[J]. IEEE Transactions on Power Delivery, 2017, 32(1): 411-419. [18] Shen Shaofei, Wang Huifang, Hu Peijun, et al.A nonparametric denoising approach for thevenin equivalent parameters estimation based on taut-string-multiresolution algorithm[C]//2017 IEEE Power & Energy Society General Meeting, Chicago, IL, USA, 2017: 1-5. [19] 张森, 王慧芳, 叶睿恺. 基于分层估计的戴维南等值阻抗在线计算方法[J]. 电力系统保护与控制, 2023, 51(12): 90-98. Zhang Sen, Wang Huifang, Ye Ruikai.Thevenin equivalent impedance online calculation method based on hierarchical estimation[J]. Power System Protection and Control, 2023, 51(12): 90-98. [20] Burchett S M, Douglas D, Ghiocel S G, et al.An optimal Thévenin equivalent estimation method and its application to the voltage stability analysis of a wind hub[J]. IEEE Transactions on Power Systems, 2018, 33(4): 3644-3652. [21] 沈绍斐. 基于就地和区域信息的自适应保护研究[D]. 杭州: 浙江大学, 2018. Shen Shaofei.Research on the local and regional area information-based adaptive protection[D]. Hangzhou: Zhejiang University, 2018. [22] 刘洪波, 刘珅诚, 盖雪扬, 等. 高比例新能源接入的主动配电网规划综述[J]. 发电技术, 2024, 45(1): 151-161. Liu Hongbo, Liu Shencheng, Gai Xueyang, et al.Overview of active distribution network planning with high proportion of new energy access[J]. Power Generation Technology, 2024, 45(1): 151-161.
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