作者机构：
[李泽文; 颜勋奇; 王梓糠; 穆利智] The Grid Security Monitoring Technology Engineering Research Center of the Ministry of Education, Changsha University of Science and Technology, Changsha;410076, China;[肖仁平] Jiangmen Power Supply Bureau, Guangdong Power Grid Co., Ltd., Jiangmen;529000, China;[李泽文; 颜勋奇; 王梓糠; 穆利智] 410076, China
通讯机构：
[Li, Z.] T;The Grid Security Monitoring Technology Engineering Research Center of the Ministry of Education, Changsha University of Science and Technology, Changsha, China
摘要：
Faulty feeder detection of the single-phase-to-ground fault in resonant grounding distribution system (GRDS) is faced with huge challenge due to weak fault current, and the existing methods indicate low reliability in some situations. For improvement, a new method based on composite factors is proposed in this paper. The composite factor is composed of transient factor and steady-state factor which are defined respectively according to transient process and steady-state component in the fault zero-sequence equivalent network. The transient factor of faulty feeder is much greater than those of healthy feeders, and the steady-state factor of faulty feeder is a constant and also much larger than those of healthy feeders when the series resistance of Peterson coil exists. However, the steady-state factors of all feeders are equal to 0 when the series resistance is short-circuited. Thus, a threshold value is constructed. By comparing the composite factors and the setting threshold, the faulty feeder can be detected. The correctness and adaptability of the proposed method are verified by simulations under various fault situations, such as different transition resistances, fault initial angles, fault distances, Gaussian white noises and compensated degrees. The tested results of experiment platform based on RTDS prove the correctness and feasibility of the proposed method.
作者机构：
[穆利智; 李泽文; 吕佳佳; 刘基典] School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha;410114, China;Foshan Electric Power Corporation, Foshan;528000, China;[胡开庚] State Grid Jining Electric Power Corporation, Jining
通讯机构：
[Li, Z.] S;School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, China
作者机构：
[李泽文; 肖仁平; 任申; 唐平; 颜勋奇] Ministry of Engineering Center for Power System Security and Supervisory Control Technology, Changsha University of Science and Technology, Changsha;410114, China;[杜昱东] Liaocheng Power Supply Company of State Grid Shandong Electric Power Co., Ltd., Liaocheng;252000, China;[李泽文; 肖仁平; 任申; 唐平; 颜勋奇] 410114, China
通讯机构：
[Li, Z.] M;Ministry of Engineering Center for Power System Security and Supervisory Control Technology, Changsha University of Science and Technology, Changsha, China
摘要：
电压暂降是电能质量问题中的一个关键难题。为了更准确地检测电压暂降发生时刻,提出了基于最大似然的自适应扩展卡尔曼滤波EKF-ML(extended Kalman filter based on maximum likelihood)算法的检测方法。首先选取不同的状态向量,在电网信号中建立2种卡尔曼滤波系统模型;其次,利用最大似然自适应优化误差协方差矩阵R和Q以及初始条件参数;最后,引入不同电能质量扰动对电压暂降进行检测证明该方法的有效性。仿真结果表明:在谐波干扰、脉冲干扰以及不同信噪比干扰情况下,EKF-ML算法能实时准确地检测电压暂降起止时间。与已有的传统方法比较,该方法适合于在未知测量噪声的条件下对电压暂降进行检测。
作者机构：
[李泽文; 贺子凝; 胡开庚; 刘基典] Ministry of Engineering Center for Power System Security and Supervisory Control Technology, Changsha University of Science and Technology, Changsha;410114, China;State Grid Xiangtan Power Supply Company, Xiangtan;411104, China;[郭田田] State Grid Liaocheng Power Supply Company, Liaocheng
通讯机构：
[Li, Z.] M;Ministry of Engineering Center for Power System Security and Supervisory Control Technology, Changsha University of Science and Technology, Changsha, China
作者机构：
[李泽文; 谭木子; 赵廷; 杜昱东] School of Electrical & Information Engineering, Changsha University of Science & Technology, Changsha;Hunan;410014, China;[彭翰川] State Grid Zhexi Hydroelectric Power Station, Yiyang;413508, China
通讯机构：
School of Electrical & Information Engineering, Changsha University of Science & Technology, Changsha, Hunan, China
摘要：
This paper presents the estimated residuals for detecting the traveling wave front using an adaptive extended Kalman filter based on the maximum likelihood (EKF-ML), which uses the maximum likelihood method to adaptively optimize the error covariance matrices and the initial conditions. In some situations, such as faults close to the bus or close to zero inception angle, or faults with high fault resistances, the transient waves can become weak and even become lost in the noise, which makes the discrimination of the traveling wave front become more difficult. Aiming at this, residuals between the observed values and the estimated values using the adaptive EKF exhibit remarkable singularities, and can be used for exactly determining the wave front. Thus, the exact arrival time of the initial wave head can be determined and then the fault distance can be calculated precisely. The effectiveness of exacting mutation feature using the proposed method has been demonstrated by a simulated instantaneous pulse. And it has been tested with different types of faults using ATP simulation. Simulation results verify that the estimated residuals are highly sensitive to traveling wave front and less sensitive to modeling uncertainty (such as noise disturbance).
作者机构：
[李泽文; 唐平; Zeng, Xiangjun; 肖仁平; 赵廷] Ministry of Engineering Center for Power System Security and Supervisory Control Technology, Changsha University of Science and Technology, Changsha;410114, China;[李泽文; 唐平; Zeng, Xiangjun; 肖仁平; 赵廷] 410114, China
通讯机构：
[Li, Z.] M;Ministry of Engineering Center for Power System Security and Supervisory Control Technology, Changsha University of Science and Technology, Changsha, China
