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为提升实验教学质量，该文设计了一种配电网单相接地故障选段实验。首先研制了接地故障实验平台，包括10 kV真型实验系统和接地电流识别装置。接着，提出了配电网接地故障选段的设计方案，并针对故障电流识别准确率低的工程普遍性问题，在深入分析健全区段与故障区段暂态零序功率累加和极性差异性的基础上，设计了一种基于遗传算法与小波包能量熵的特征频带优选的接地故障电流识别方法。实验结果表明，所提方法具有自适应、免阈值的优点，相对于其他文献方法具有较高的识别准确率。最后，针对不同的课程需求，设计了层次性实验，在提升学生的实践操作技能和增强实验教学效果方面发挥了积极作用。
Abstract：[Objective] A single-phase grounding fault is the most frequent type of fault in distribution networks, and identifying the fault accurately and locating the fault section for the safe operation of power networks is crucial. However, because of small fault current, weak fault characteristics, and poor dispersion, the accuracy of fault location in engineering practice is low. In order to enhance the quality of experimental teaching, students' cognition of single-phase grounding fault in distribution networks, and their practical analytical skills, this paper presents an experimental design scheme for the resonant grounding fault segment in distribution networks. [Methods] First, the design method of the single-phase grounding fault experiment platform is described, including the components of the 10 kV true type experiment system and the hardware and software designs of the single-phase fault grounding current identification terminal to build a real experimental environment for the research. Second, the design scheme of the distribution network grounding fault section is proposed. After an in-depth analysis of the polarity differences between the transient zero-sequence signals in the healthy section and the faulty section, it is found that when transient zero-sequence power is directly calculated, misjudgment will occur because of the influence of arc suppression coil compensation and noise interference. However, some frequency band information of the zero-sequence power contains characteristic information that can effectively suppress the interference. Based on this, the transient zero-sequence power is decomposed by a wavelet packet algorithm, in which the frequency band with strong energy entropy can stably reflect the state characteristics of the line. Considering the randomness and uncertainty of the fault arc and the presence of field noise, the high-entropy characteristic frequency bands of each fault sample are not the same, and the number of characteristic frequency bands available for selection is large. Therefore, this paper further proposes a feature frequency band optimization method based on a genetic algorithm and wavelet packet energy entropy. In the offline stage, the genetic algorithm is used to screen the massive historical data and optimize the selection of feature frequency bands to improve the identification accuracy of the fault section. In the single calculation stage, the five frequency bands with the highest wavelet packet energy entropy are selected as the characteristic frequency bands, and then, the fault characteristic frequency bands with strong characterization ability are determined by intersection operation. This method can effectively suppress the noise interference and enhance the identification performance of the fault section. [Results] Experimental results show that the proposed method is highly adaptive, requires no threshold in ground fault current identification, and achieves an accuracy of 95.24%. Compared with other methods in the literature, the proposed method can maintain higher recognition performance under various working conditions. Finally, hierarchical experiment schemes are designed according to different curriculum requirements for students to gradually master the whole process from fault mechanism analysis to advanced intelligent identification methods. [Conclusions] The experimental platform and single-phase grounding fault identification method not only improve the students' hands-on and engineering application capabilities but also lay the foundation for further research and application of single-phase grounding fault detection technology in distribution networks and provide an innovative practical teaching model for the cultivation of talent in the field of power engineering.
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Basic Information:
DOI：10.16791/j.cnki.sjg.2025.07.005
China Classification Code:TM862
Citation Information:
[1]高伟,郑子杰,李育凤等.基于暂态零序功率特性的配电网单相接地故障选段实验设计[J].实验技术与管理,2025,42(07):34-42.DOI:10.16791/j.cnki.sjg.2025.07.005.
Fund Information:
福建省教育厅2022年本科高校教育教学研究项目(重大项目)(FBJG20220284); 福建省自然科学基金项目(2021J01633)