Strategy to Precisely Locate Voltage Sag Source in Active Distribution Grid with Data Measured by Limited Power Quality Observations
Chen Rusi1, 2, Lin Tao1, 3, Bi Ruyu1, Xu Xialing4, Qi Qing5
1. School of Electrical Engineering Wuhan University Wuhan 430072 China; 2. State Grid Hubei Electric Power Research Institute Wuhan 430077 China; 3. Solar Energy Efficient Use Collaborative Innovation Center of Hubei Province Wuhan 430068 China; 4. Central China Branch of State Grid Corporation of China Wuhan 430077 China; 5. State Grid Beijing Electric Power Company Beijing 100031 China
Abstract:Precise locating of voltage sag source has important significance in promoting power supply dependability and clarifying responsibilities. As a hot research spot, a series of researches were carried out with the help of power quality (PQ) monitoring system and distribution automation system in recent years. However, existing locating methods fail to distinguish the type of sag source and need to search all the buses. Moreover, they are merely applied to traditional radial distribution grid with single power supply, and the locating accuracy is non-ideal as inaccurate estimation of transition resistance. In this paper, a precise locating strategy applied to active distribution grid with multiple distributed generators, is put forward. Firstly, the potential distribution area of voltage sag source is narrowed by the directions of sequence power increments. Then, type of sag source is identified to guide locating. For voltage sag caused by short-circuit fault, a step-by-step optimization model, which aims at minimizing the differences between the measured data and the calculated data at limited observations, is established. As the basis, impacts of distributed generators and transition resistance are considered in short-circuit calculation. Finally, based on the modified IEEE 34-node benchmark, the validity and superiorities of the proposed strategy are verified.
陈汝斯,林涛,毕如玉, 徐遐龄, 齐清. 基于有限量测数据的主动配电网电压暂降源精确定位策略[J]. 电工技术学报, 2019, 34(zk1): 312-320.
Chen Rusi, Lin Tao, Bi Ruyu, Xu Xialing, Qi Qing. Strategy to Precisely Locate Voltage Sag Source in Active Distribution Grid with Data Measured by Limited Power Quality Observations. Transactions of China Electrotechnical Society, 2019, 34(zk1): 312-320.
[1] 马玲玲, 杨军, 付聪, 等. 电动汽车充放电对电网影响研究综述[J]. 电力系统保护与控制, 2013, 41(3): 140-148. Ma Lingling, Yang Jun, Fu Cong, et al.Review on impact of electric car charging and discharging on power grid[J]. Power System Protection and Control, 2013, 41(3): 140-148. [2] 何秋生, 徐磊, 吴雪雪. 锂电池充电技术综述[J]. 电源技术, 2013, 37(8): 1464-1466. He Qiusheng, Xu Lei, Wu Xuexue.Review of lithium battery charging technology[J]. Chinese Journal of Power Sources, 2013, 37(8): 1464-1466. [3] 谢长君, 费亚龙, 曾春年, 等. 基于无迹粒子滤波的车载锂离子电池状态估计[J]. 电工技术学报, 2018, 33(17): 3958-3964. Xie Changjun, Fei Yalong, Zeng Chunnian, et al.State-of-charge estimation of lithium-ion battery using unscented particle filter in vehicle[J]. Transa- ctions of China Electrotechnical Society, 2018, 33(17): 3958-3964. [4] 刘念, 唐霄, 段帅, 等. 考虑动力电池梯次利用的光伏换电站容量优化配置方法[J]. 中国电机工程学报, 2013, 33(4): 34-44. Liu Nian, Tang Xiao, Duan Shuai, et al.Capacity optimization method for PV-based battery swapping stations considering second-use of electric vehicle batteries[J]. Proceedings of the CSEE, 2013, 33(4): 34-44. [5] 刘坚. 电动汽车退役电池储能应用潜力及成本分析[J]. 储能科学与技术, 2017, 6(2): 243-249. Liu Jian.Second use potential of retired EV batteries in power system and associated cost analysis[J]. Energy Storage Science and Technology, 2017, 6(2): 243-249. [6] 孙冬, 许爽. 梯次利用锂电池健康状态预测[J]. 电工技术学报, 2018, 33(9): 2121-2129. Sun Dong, Xu Shuang.State of health prediction of second-use lithium-ion battery[J]. Transactions of China Electrotechnical Society, 2018, 33(9): 2121-2129. [7] 吴盛军, 袁晓冬, 徐青山, 等. 锂电池健康状态评估综述[J]. 电源技术, 2017, 41(12): 1788-1791. Wu Shengjun, Yuan Xiaodong, Xu Qingshan, et al.Review on lithium-ion battery health state assess- ment[J]. Chinese Journal of Power Sources, 2017, 41(12): 1788-1791. [8] Ning Gang, White R E, Popov B N.A generalized cycle life model of rechargeable Li-ion batteries[J]. Electrochimica Acta, 2006, 51(10): 2012-2022. [9] 黄业伟. 电动汽车锂离子动力电池健康状态估计方法研究[D]. 合肥: 合肥工业大学, 2014. [10] Bhangu B S, Bentley P, Stone D A, et al.Nonlinear observers for predicting state-of-charge and state-of- health of lead-acid batteries for hybrid-electric vehicles[J]. IEEE Transactions on Vehicular Tech- nology, 2005, 54(3): 783-794. [11] 高安同, 张金, 周生, 等. 基于卡尔曼滤波算法的锂离子电池荷电状态估算[J]. 电子技术应用, 2014, 40(5): 65-67. Gao Antong, Zhang Jin, Zhou Sheng, et al.State of charge estimation of liion battery based on Kalman filter algorithm[J]. Application of Electronic Tech- nique, 2014, 40(5): 65-67. [12] 孙培坤. 电动汽车动力电池健康状态估计方法研究[D]. 北京: 北京理工大学, 2016. [13] 黎火林, 苏金然. 锂离子电池循环寿命预计模型的研究[J]. 电源技术, 2008, 32(4): 242-246. Li Huolin, Su Jinran.Cycle-life prediction model- studies of lithium-ion batteries[J]. Chinese Journal of Power Sources, 2008, 32(4): 242-246. [14] 杨刘倩, 詹昌辉, 卢雪梅. 电动汽车锂电池健康状态估算方法研究[J]. 电源技术, 2016, 40(4): 823-825, 853. Yang Liuqian, Zhan Changhui, Lu Xuemei.Research on estimation method of healthy status for EV lithium battery[J]. Chinese Journal of Power Sources, 2016, 40(4): 823-825, 853. [15] 连湛伟, 石欣, 克潇, 等. 电动汽车充换电站动力电池全寿命周期在线检测管理系统[J]. 电力系统保护与控制, 2014, 42(12): 137-142. Lian Zhanwei, Shi Xin, Ke Xiao, et al.The whole life cycle on-line detection and management system of power battery in the electric vehicle charging and exchanging station[J]. Power System Protection and Control, 2014, 42(12): 137-142. [16] 李晓宇, 朱春波, 魏国, 等. 基于分数阶联合卡尔曼滤波的磷酸铁锂电池简化阻抗谱模型参数在线估计[J]. 电工技术学报, 2016, 31(24): 141-149. Li Xiaoyu, Zhu Chunbo, Wei Guo, et al.Online parameter estimation of a simplified impedance spectroscopy model based on the fractional joint Kalman filter for LiFePO4 battery[J]. Transactions of China Electrotechnical Society, 2016, 31(24): 141-149. [17] 刘树林, 崔纳新, 李岩, 等. 基于分数阶理论的车用锂离子电池建模及荷电状态估计[J]. 电工技术学报, 2017, 32(4): 189-195. Liu Shulin, Cui Naxin, Li Yan, et al.Modeling and state of charge estimation of lithium-ion battery based on theory of fractional order for electric vehicle[J]. Transactions of China Electrotechnical Society, 2017, 32(4): 189-195. [18] 张聪, 张祥文, 夏俊荣, 等. 电动汽车实时可调度容量评估方法研究[J]. 电力系统保护与控制, 2015, 43(22): 99-106. Zhang Cong, Zhang Xiangwen, Xia Junrong, et al.Research on estimation of electric vehicles real-time schedulable capacity[J]. Power System Protection and Control, 2015, 43(22): 99-106. [19] 杨帆, 乔艳龙, 甘德刚, 等. 不同充电模式对锂离子电池极化特性影响[J]. 电工技术学报, 2017, 32(12): 171-178. Yang Fan, Qiao Yanlong, Gan Degang, et al.Lithium-ion battery polarization characteristics at different charging modes[J]. Transactions of China Electrotechnical Society, 2017, 32(12): 171-178. [20] Guan Pengjian, Liu Lin, Lin Xianke.Simulation and experiment on solid electrolyte interphase (SEI) morphology evolution and lithium-ion diffusion[J]. Journal of the Electrochemical Society, 2015, 162(9): A1798-A1808. [21] 程冰冰. LiCoO2锂离子电池存储性能衰退机理及改善研究[D]. 长沙: 国防科学技术大学, 2015. [22] 林娅, 陈则王. 锂离子电池剩余寿命预测研究综述[J]. 电子测量技术, 2018, 41(4): 29-35. Lin Ya, Chen Zewang.Review of remaining life prediction for lithium-ion batteries[J]. Electronic Measurement Technology, 2018, 41(4): 29-35. [23] 明海, 明军, 邱景义, 等. 基于非锂金属负极的锂离子全电池[J]. 化学进展, 2016, 28(增刊2): 204-218. Ming Hai, Ming Jun, Qiu Jingyi, et al.Lithium-ion full batteries based on the anode of non-metallic lithium[J]. Progress in Chemistry, 2016, 28(S2): 204-218. [24] 李广地, 吕浩华, 袁军, 等. 动力锂电池的寿命研究综述[J]. 电源技术, 2016, 40(6): 1312-1314. Li Guangdi, Lü Haohua, Yuan Jun, et al.Review of life research on electric vehicle Li-ion cell[J]. Chinese Journal of Power Sources, 2016, 40(6): 1312-1314. [25] 张培新, 汪静伟, 黄亮, 等. 锂离子电池硅基负极材料研究现状与发展趋势[J]. 深圳大学学报(理工版), 2014, 31(5): 441-451. Zhang Peixin, Wang Jingwei, Huang Liang, et al.Research status and development trend on Si-based anode materials of lithium ion batteries[J]. Journal of Shenzhen University Science and Engineering, 2014, 31(5): 441-451.