A Fast Screening Method for the High-Risk Faults with Transient Voltage Instability in Receiving-End Power Grids Interconnected with New Energy
Yang Jinzhou1, Li Yecheng1,2, Xiong Hongtao3, Kong He1, Xue Ancheng1
1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Source North China Electric Power University Beijing 102206 China; 2. State Grid Jining Power Supply Company Jining 272000 China; 3. State Grid Zhejiang Electric Power Research Institute Hangzhou 310014 China
Abstract：The receiving-end power grid interconnected with large-scale new energy lack reactive power support from local conventional generators, so that transient voltage stability problems are particularly prominent, easy to cause grid blackout. However, existing transient voltage stability analysis methods are mainly based on time-domain simulations, and most of these methods have large computational volume and high complexity, which are not fast enough to locate the critical fault point in time in the actual power grids. On the other hand, most of the existing studies related to locating critical fault points of power grids utilize graph-theoretic concepts to construct indexes. Although these methods are faster in computation, most of them lack relevant physical meanings, making it difficult to accurately identify the critical fault point of the actual large power grid. In view of this, this paper analyzes the degree of influence of points on the transient voltage stability of the grid based on the weighted topology and transient parameters of the grid, combined with the impedance matrix, in order to quickly screen high-risk fault points. Specifically, firstly, an index reflecting the degree of influence of node faults on the transient voltages of power grid (degree index, also the point influence factor, FAC) is proposed, which can be used for fast screening of high-risk critical fault points; secondly, for the line fault points, an ascending matrix is constructed to calculate their FAC, and the point influence factor array forms a screening method for the whole grid of high-risk critical fault points with high transient voltage instability risk; lastly, the above screening method is applied to the improved IEEE 39 bus test system and the actual receiving-end grid. In the improved IEEE 39-bus system, firstly, the FAC of the bus nodes are calculated, and it is concluded that bus 16 has the highest FAC of 0.350 0, and the indexes are compared with the average minimum voltage (UAVL) of the grid under fault and critical clearing time (CCT) to prove its validity; secondly, the FAC of the equivalent buses on the line are calculated, and it is found that the FAC in the line is not the highest, and the color rendering of the system shows the area around the bus 16 has a higher level of risk; furthermore, the effects of load characteristics and fault types on FAC are also considered; finally, the computational efficiency of the screening methods is analyzed and compared. In the actual large receiving-end grid, the FAC of the buses are calculated, and it can be seen that the FAC of the TZ, OH and NY are higher, which are 0.325 8, 0.303 9 and 0.294 3, respectively, and the simulation results also proved that these nodes play a key role in the transient voltage stability of the whole grid. The main work and conclusions of this paper are as follows: (1) this paper attributes the change of voltage during transient process to the change of impedance based on the supporting role of impedance on voltage, and accordingly proposes the FAC. (2) This paper puts forward a way of thinking to construct the ascending matrix in order to calculate the FAC of the line fault point and summarize it as a fast screening method for the critical fault point. (3) Simulation results show that the proposed FAC index can effectively reflect the degree of influence of fault point on the transient voltage, and the screening method using the FAC can quickly screen the high-risk faults and visualize the results, which has a certain degree of engineering practicability, and can provide a theoretical basis for the subsequent development of security & control strategies.
杨金洲, 李业成, 熊鸿韬, 孔贺, 薛安成. 新能源接入的受端电网暂态电压失稳高风险故障快速筛选[J]. 电工技术学报, 2024, 39(21): 6746-6758.
Yang Jinzhou, Li Yecheng, Xiong Hongtao, Kong He, Xue Ancheng. A Fast Screening Method for the High-Risk Faults with Transient Voltage Instability in Receiving-End Power Grids Interconnected with New Energy. Transactions of China Electrotechnical Society, 2024, 39(21): 6746-6758.
[1] 项胜, 何怡刚, 吴可汗. 基于分形理论的国内大停电分析[J]. 电工技术学报, 2013, 28(增刊2): 367-371. Xiang Sheng, He Yigang, Wu Kehan.Blackout analysis of domestic power based on fractal theory[J]. Transactions of China Electrotechnical Society, 2013, 28(S2): 367-371. [2] 孙华东, 许涛, 郭强, 等. 英国“8·9”大停电事故分析及对中国电网的启示[J]. 中国电机工程学报, 2019, 39(21): 6183-6192. Sun Huadong, Xu Tao, Guo Qiang, et al.Analysis on blackout in great Britain power grid on August 9th, 2019 and its enlightenment to power grid in China[J]. Proceedings of the CSEE, 2019, 39(21): 6183-6192. [3] 胡秦然, 丁昊晖, 陈心宜, 等. 美国加州2020年轮流停电事故分析及其对中国电网的启示[J]. 电力系统自动化, 2020, 44(24): 11-18. Hu Qinran, Ding Haohui, Chen Xinyi, et al.Analysis on rotating power outage in California, USA in 2020 and its enlightenment to power grid of China[J]. Automation of Electric Power Systems, 2020, 44(24): 11-18. [4] 唐欣, 蔡明君, 唐惟楚, 等. 辐射型直流配电网母线电压跌落峰值的定量计算方法[J]. 电工技术学报, 2022, 37(12): 3108-3116. Tang Xin, Cai Mingjun, Tang Weichu, et al.Quantitative calculation method of bus voltage sag peak value in radial DC distribution network[J]. Transactions of China Electrotechnical Society, 2022, 37(12): 3108-3116. [5] 姜涛, 李雪, 李国庆, 等. 含多端柔性直流的交直流电力系统静态电压稳定域构建方法[J]. 电工技术学报, 2022, 37(7): 1746-1759. Jiang Tao, Li Xue, Li Guoqing, et al.A predictor-corrector algorithm for forming voltage stability region of hybrid AC/DC power grid with inclusion of VSC-MTDC[J]. Transactions of China Electrotechnical Society, 2022, 37(7): 1746-1759. [6] 全国电网运行与控制标准化技术委员会. 电力系统安全稳定计算技术规范: DL/T 1234—2013[S]. 北京: 中国电力出版社, 2013. [7] 中国南方电网电力调度通信中心. 南方电网安全稳定计算分析导则: Q/CSG 11004—2009[S]. 广州: 中国南方电网公司, 2009. [8] 薛安成, 周健, 刘瑞煌, 等. 采用多二元表判据的实用暂态电压稳定裕度指标研究[J]. 中国电机工程学报, 2018, 38(14): 4117-4125, 4317. Xue Ancheng, Zhou Jian, Liu Ruihuang, et al.A new practical transient voltage stability margin index based on multiple-two-element notation criterion[J]. Proceedings of the CSEE, 2018, 38(14): 4117-4125, 4317. [9] 王东旭, 乐健, 刘开培, 等. 基于虚拟节点的复杂电网电压跌落随机评估方法[J]. 电工技术学报, 2011, 26(8): 190-197. Wang Dongxu, Le Jian, Liu Kaipei, et al.Stochastic assessment method of voltage dip in complex power grid based on virtual bus[J]. Transactions of China Electrotechnical Society, 2011, 26(8): 190-197. [10] Watts D J, Strogatz S H.Collective dynamics of ‘small-world' networks[J]. Nature, 1998, 393(6684): 440-442. [11] 孟仲伟, 鲁宗相, 宋靖雁. 中美电网的小世界拓扑模型比较分析[J]. 电力系统自动化, 2004, 28(15): 21-24, 29. Meng Zhongwei, Lu Zongxiang, Song Jingyan.Comparison analysis of the small-world topological model of Chinese and American power grids[J]. Automation of Electric Power Systems, 2004, 28(15): 21-24, 29. [12] Crucitti P, Latora V, Marchiori M.A topological analysis of the Italian electric power grid[J]. Physica A: Statistical Mechanics and Its Applications, 2004, 338(1/2): 92-97. [13] Mishkovski I, Biey M, Kocarev L.Vulnerability of complex networks[J]. Communications in Nonlinear Science and Numerical Simulation, 2011, 16(1): 341-349. [14] 谭玉东, 李欣然, 蔡晔, 等. 基于电气距离的复杂电网关键节点识别[J]. 中国电机工程学报, 2014, 34(1): 146-152. Tan Yudong, Li Xinran, Cai Ye, et al.Critical node identification for complex power grid based on electrical distance[J]. Proceedings of the CSEE, 2014, 34(1): 146-152. [15] Motter A E, Lai Yingcheng.Cascade-based attacks on complex networks[J]. Physical Review E, 2002, 66(6): 065102. [16] Kinney R, Crucitti P, Albert R, et al.Modeling cascading failures in the North American power grid[J]. The European Physical Journal B -Condensed Matter and Complex Systems, 2005, 46(1): 101-107. [17] 王涛, 李渝, 顾雪平, 等. 电网关键线路序元搜索方法[J]. 电工技术学报, 2016, 31(2): 153-162. Wang Tao, Li Yu, Gu Xueping, et al.Study of grid's key line sequence search method[J]. Transactions of China Electrotechnical Society, 2016, 31(2): 153-162. [18] 单政博. 电网重要节点、脆弱线路及骨干网架识别研究[D]. 杭州: 浙江大学, 2017. Shan Zhengbo.Research on identifications of important node, vulnerable transmission line and backbone grid[D]. Hangzhou: Zhejiang University, 2014. [19] Carreras B A, Newman D E, Dobson I, et al.Evidence for self-organized criticality in a time series of electric power system blackouts[J]. IEEE Transactions on Circuits and Systems I: Regular Papers, 2004, 51(9): 1733-1740. [20] Crucitti P, Latora V, Marchiori M.Model for cascading failures in complex networks[J]. Physical Review E, 2004, 69(4): 045104. [21] Rosas-Casals M, Valverde S, Solé R V.Topological vulnerability of the European power grid under errors and attacks[J]. International Journal of Bifurcation and Chaos, 2007, 17(7): 2465-2475. [22] 顾雪平, 刘彤, 李少岩, 等. 用于未来态预测的电网运行断面时空相似性挖掘[J]. 电工技术学报, 2022, 37(23): 6145-6156. Gu Xueping, Liu Tong, Li Shaoyan, et al.Temporal and spatial similarity mining of power grid running section for future state prediction[J]. Transactions of China Electrotechnical Society, 2022, 37(23): 6145-6156. [23] 李雪, 姜涛, 李国庆, 等. 基于相关增益的电压稳定关键注入区域识别[J]. 电工技术学报, 2018, 33(4): 739-749. Li Xue, Jiang Tao, Li Guoqing, et al.Voltage stability critical injection area determination via cross-relative gain[J]. Transactions of China Electrotechnical Society, 2018, 33(4): 739-749. [24] 王涛, 李渝, 顾雪平, 等. 考虑地理分区边界优化的电网关键输电断面辨识[J]. 电工技术学报, 2014, 29(4): 220-228, 245. Wang Tao, Li Yu, Gu Xueping, et al.Identification of the key transmission sections considering optimization of geographical partition boundary for power grids[J]. Transactions of China Electrotechnical Society, 2014, 29(4): 220-228, 245. [25] 徐林, 王秀丽, 王锡凡. 电气介数及其在电力系统关键线路识别中的应用[J]. 中国电机工程学报, 2010, 30(1): 33-39. Xu Lin, Wang Xiuli, Wang Xifan.Electric betweenness and its application in vulnerable line identification in power system[J]. Proceedings of the CSEE, 2010, 30(1): 33-39. [26] 李昌超, 康忠健, 于洪国, 等. 基于PageRank改进算法的电力系统关键节点识别[J]. 电工技术学报, 2019, 34(9): 1952-1959. Li Changchao, Kang Zhongjian, Yu Hongguo, et al.Identification method of key nodes in power system based on improved PageRank algorithm[J]. Transactions of China Electrotechnical Society, 2019, 34(9): 1952-1959. [27] 谭玉东. 复杂电力系统脆弱性评估方法研究[D]. 长沙: 湖南大学, 2013. Tan Yudong.Research on complex power system vulnerability assessment methods[D]. Changsha: Hunan University, 2013. [28] 向洁, 蔡静谊, 刘小林, 等. 基于改进奇异值分解法的电力系统弱节点研究[J]. 电气技术, 2012(8): 55-58. Xiang Jie, Cai Jingyi, Liu Xiaolin, et al.Research on weak node of power system based on modified singular value decomposition[J]. Electrical Engineering, 2012(8): 55-58. [29] 胡臻, 李欣然, 刘光晔, 等. 基于稳定影响度指标的电压稳定脆弱点分析[J]. 电工技术学报, 2017, 32(7): 150-157. Hu Zhen, Li Xinran, Liu Guangye, et al.Analysis of voltage fragility area based on the stability influence index[J]. Transactions of China Electrotechnical Society, 2017, 32(7): 150-157. [30] 张伯明, 陈寿孙, 严正. 高等电力网络分析[M]. 2版. 北京: 清华大学出版社, 2007: 89-117. [31] Sherman J, Morrison W J.Adjustment of an inverse matrix corresponding to a change in one element of a given matrix[J]. The Annals of Mathematical Statistics, 1950, 21(1): 124-127. [32] 丁明, 过羿, 张晶晶, 等. 基于效用风险熵权模糊综合评判的复杂电网节点脆弱性评估[J]. 电工技术学报, 2015, 30(3): 214-223. Ding Ming, Guo Yi, Zhang Jingjing, et al.Node vulnerability assessment for complex power grids based on effect risk entropy-weighted fuzzy comprehensive evaluation[J]. Transactions of China Electrotechnical Society, 2015, 30(3): 214-223. [33] 栗然, 靳保源, 张凡, 等. 基于图谱理论的电力系统关键节点识别方法[J]. 电力系统保护与控制, 2018, 46(11): 14-22. Li Ran, Jin Baoyuan, Zhang Fan, et al.Research on identification of key nodes in power system based on spectral graph theory[J]. Power System Protection and Control, 2018, 46(11): 14-22. [34] 杨文辉, 毕天姝, 黄少锋, 等. 基于电网生存性评估的关键线路识别方法[J]. 中国电机工程学报, 2011, 31(7): 29-35. Yang Wenhui, Bi Tianshu, Huang Shaofeng, et al.An approach for critical lines identification based on the survivability of power grid[J]. Proceedings of the CSEE, 2011, 31(7): 29-35.
2024, Vol. 39 
