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学者姓名：高伟
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油纸绝缘作为电力变压器中的主绝缘设备,在工业生产和电力传输应用中尤为重要,为验证油纸绝缘的性能状态,该文研制了基于介质响应原理的现场可编程电力电子控制实验平台.平台以LabVIEW编程环境和三电极测试装置作为载体,采用状态机框架设计了回复电压谱与极化谱测量流程,并嵌入聚类云模型算法实现油纸绝缘状态精准分类.该实验平台可促进理论知识与实践经验相结合的教学模式革新,满足实验探索、科学研究等多层次需求.
Keyword ：
回复电压测试 回复电压测试 实验平台设计 实验平台设计 数字编程控制 数字编程控制 油纸绝缘 油纸绝缘
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| GB/T 7714 | 邹阳 , 黄煜 , 方梦泓 et al. 基于介质响应原理的变压器油纸绝缘测试实验平台设计 [J]. | 实验技术与管理 , 2025 , 42 (1) : 176-183 . |
| MLA | 邹阳 et al. "基于介质响应原理的变压器油纸绝缘测试实验平台设计" . | 实验技术与管理 42 . 1 (2025) : 176-183 . |
| APA | 邹阳 , 黄煜 , 方梦泓 , 石松浩 , 姚雨佳 , 高伟 . 基于介质响应原理的变压器油纸绝缘测试实验平台设计 . | 实验技术与管理 , 2025 , 42 (1) , 176-183 . |
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针对大部分光伏电站电弧故障历史数据缺乏的问题,本文在采集电弧超声信号并分析其特点后,提出一种基于超声波传感器与孤立森林的光伏系统串联电弧故障诊断方法.首先,利用S变换将发生串联电弧故障时的超声波暂态电压信号转化至时频域;接着,利用Teager能量算子放大频谱差异性,并通过时频熵提取电弧故障时频域特征;最后,基于动态阈值与孤立森林实现电弧故障诊断且无需历史数据.实验结果表明,所提方法能准确识别串联电弧故障,诊断准确率达到 97.25%,且具备较强的抗干扰能力.
Keyword ：
S变换 S变换 光伏系统 光伏系统 孤立森林 孤立森林 电弧故障诊断 电弧故障诊断 超声波信号 超声波信号
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| GB/T 7714 | 黄晨昊 , 高伟 . 基于超声波传感器与孤立森林的光伏系统串联电弧故障诊断方法 [J]. | 电气技术 , 2025 , 26 (5) : 10-16,26 . |
| MLA | 黄晨昊 et al. "基于超声波传感器与孤立森林的光伏系统串联电弧故障诊断方法" . | 电气技术 26 . 5 (2025) : 10-16,26 . |
| APA | 黄晨昊 , 高伟 . 基于超声波传感器与孤立森林的光伏系统串联电弧故障诊断方法 . | 电气技术 , 2025 , 26 (5) , 10-16,26 . |
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目前剩余电流动作保护装置(RCDs)仅依靠固定阈值作为动作判据,在参数配合整定不合理、谐波含量大和高频电弧脉冲等因素的影响下,存在拒动和误动的风险,且无法有效辨识出真正的触电事件.对此,提出了一种基于小波包分解和特征分量动态优选的新型RCD动作判据,可快速识别出常规接地故障、触电、电弧等多种类型的故障.首先,利用高阶统计量中对信号冲击敏感的峭度值捕捉故障起始时刻,并通过计算该时刻前后各一周波差分剩余电流信号的能量比,以实时甄别异常状态.其次,收集故障前一周波和故障启动后三周波的差分剩余电流信号进行小波包分解,融合各节点分量的峭度值、小波包能量比与样本熵特征为动态优选指标(DOI),并结合各分量DOI的贡献度重构低频与高频信号,以突出各故障类型在不同频段电流波形中的故障特征信息.最后,提取不同重构信号的电气量特征,透过双层链式规则实现故障精准分类.该方法已在RCD样机上进行验证,实验结果表明,其在低压交流配电网的串联电弧、接地电弧、触电故障以及常规接地故障检测中表现优异,识别率达到97.52%,平均诊断时间为79.6 ms,能够满足RCDs所要求的灵敏性和可靠性,有效提升了RCDs的实际应用价值.
Keyword ：
串联电弧 串联电弧 剩余电流动作保护装置 剩余电流动作保护装置 小波包分解 小波包分解 特征分量动态优选 特征分量动态优选 触电故障 触电故障
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| GB/T 7714 | 高伟 , 陈渊隆 , 黄天富 . 一种基于小波包分解和特征分量动态优选的剩余电流动作保护方法 [J]. | 仪器仪表学报 , 2025 , 46 (1) : 311-323 . |
| MLA | 高伟 et al. "一种基于小波包分解和特征分量动态优选的剩余电流动作保护方法" . | 仪器仪表学报 46 . 1 (2025) : 311-323 . |
| APA | 高伟 , 陈渊隆 , 黄天富 . 一种基于小波包分解和特征分量动态优选的剩余电流动作保护方法 . | 仪器仪表学报 , 2025 , 46 (1) , 311-323 . |
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In order to address the challenges posed by weak and variable high-impedance fault signals and limited data availability in practical distribution networks, a novel method for detecting high-impedance faults is proposed. Initially, a multi-head variational autoencoder model based on squeeze-excitation networks is employed to augment the small sample dataset. Subsequently, the data are filtered, and the temporal and frequency domain features are extracted, respectively. Considering the weak characteristics of high impedance fault features and the limitations of the proliferation model in generating comprehensive and effective fault features, a categorical boosting algorithm based on the gradient harmonized mechanism (GHM-CatBoost) is introduced. The GHM-CatBoost algorithm incorporates a gradient harmonized mechanism loss function to address the imbalance in attention between easily distinguishable and challenging samples, thereby mitigating the issue of overfitting. The research findings suggest that the data proliferation model can produce fault samples with a blend of simulation data diversity and measured data randomness, thereby enhancing the richness of the dataset. Furthermore, the fault recognition accuracy achieved by the proposed GHM-CatBoost model is notably high at 97.21%, outperforming its counterpart classifier model. Moreover, the efficacy of the proposed approach is validated through rigorous testing and comparative analysis. © 2025 Science Press. All rights reserved.
Keyword ：
Adaptive boosting Adaptive boosting Fault detection Fault detection Frequency domain analysis Frequency domain analysis Image segmentation Image segmentation Network coding Network coding Variational techniques Variational techniques
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| GB/T 7714 | Gao, Wei , He, Wenxiu , Guo, Moufa et al. Detection Method of High-impedance Fault in Distribution Network Based on Uneven Small Samples from Actual Measurements [J]. | High Voltage Engineering , 2025 , 51 (3) : 1135-1144 . |
| MLA | Gao, Wei et al. "Detection Method of High-impedance Fault in Distribution Network Based on Uneven Small Samples from Actual Measurements" . | High Voltage Engineering 51 . 3 (2025) : 1135-1144 . |
| APA | Gao, Wei , He, Wenxiu , Guo, Moufa , Bai, Hao . Detection Method of High-impedance Fault in Distribution Network Based on Uneven Small Samples from Actual Measurements . | High Voltage Engineering , 2025 , 51 (3) , 1135-1144 . |
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考虑到传统的基于电磁辐射(electromagnetic radiation,EMR)信号的光伏阵列电弧故障定位方法存在采样条件严苛、定位精度低等问题,提出一种基于网格指纹匹配的电弧故障定位新方法.首先,使用低采样率获取电弧EMR信号,并提取其均方根值作为代表EMR强度的特征指标.然后,利用BP神经网络(back propagation neural network,BPNN)挖掘辐照度、信号接收距离与电弧EMR信号强度的内在联系,建立预测模型.接着,根据BPNN输出的双天线阵列与电弧间的预测距离,利用三角定位法初步求得电弧所在区域.最后,网格化划分电弧所在区域的光伏组件,生成网格指纹信息,并将预测距离与指纹信息最匹配的网格的中心坐标作为电弧发生位置的最终预测坐标.实验结果表明,所提算法具备良好的定位能力与适应性,对电弧故障定位的平均绝对误差为0.306 m,在定位精度与经济性上均优于EMR衰减模型定位法.
Keyword ：
BP神经网络 BP神经网络 光伏阵列 光伏阵列 电弧故障定位 电弧故障定位 电磁辐射 电磁辐射 网格指纹匹配 网格指纹匹配
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| GB/T 7714 | 金辉 , 高伟 , 林亮世 et al. 基于网格指纹匹配的光伏阵列电弧故障定位方法 [J]. | 高电压技术 , 2024 , 50 (2) : 834-845 . |
| MLA | 金辉 et al. "基于网格指纹匹配的光伏阵列电弧故障定位方法" . | 高电压技术 50 . 2 (2024) : 834-845 . |
| APA | 金辉 , 高伟 , 林亮世 , 杨耿杰 . 基于网格指纹匹配的光伏阵列电弧故障定位方法 . | 高电压技术 , 2024 , 50 (2) , 834-845 . |
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为了加强配电网自动化技术课程建设,提出基于虚实协同配合的实验教学方案.以"情景互动、探究创新"为实验教学理念,将课堂理论、虚拟仿真和物理仿真三者紧密结合.从需求导向出发,设计了四个渐进式实验,通过沉浸式教学,让学生了解配电网和开关设备的结构形态,掌握配电网运行、故障与保护算法的原理,培养学生的创新思维和创新设计能力.最后,建立主、客观评价相结合的综合评价体系,对学生参与实验的每个环节进行评价,通过收集反馈信息,持续改进评价体系.
Keyword ：
实验教学 实验教学 物理仿真 物理仿真 虚拟仿真 虚拟仿真 配电网 配电网
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| GB/T 7714 | 林宝全 , 高伟 , 郭谋发 et al. 虚实协同的"配电网自动化技术"实验项目建设 [J]. | 电气电子教学学报 , 2024 , 46 (2) : 216-220 . |
| MLA | 林宝全 et al. "虚实协同的"配电网自动化技术"实验项目建设" . | 电气电子教学学报 46 . 2 (2024) : 216-220 . |
| APA | 林宝全 , 高伟 , 郭谋发 , 谢楠 . 虚实协同的"配电网自动化技术"实验项目建设 . | 电气电子教学学报 , 2024 , 46 (2) , 216-220 . |
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The complexity and uncertainty of vibration signals from distribution transformers pose significant challenges for diagnosing mechanical faults. To address this, this paper proposes a novel fault diagnosis model for distribution transformers, which combines a cross-domain fusion multi-scale convolutional autoencoder (CFMS-CAE) with an open-set domain adaptation classifier (OSDA-C). Specifically, in order to extract more comprehensive features, a convolutional autoencoder (CAE) model based on multi-output objectives is constructed to extract the timefrequency domain characteristics of transformer vibration signals. Multiple-scale convolutional layers are incorporated into the convolutional autoencoder to enable multi-range feature extraction. Additionally, parameter optimization is achieved using the crayfish optimization algorithm (COA). Subsequently, an open-set domain adaptation module is integrated into the convolutional neural network classifier to establish boundaries for each category and facilitate the identification of transformer fault categories, including unknown-type faults. The experimental results demonstrate that the proposed method is effective for fault identification in both drytype and oil-immersed transformers, with average accuracy reaching 99.35% and 99.62%, respectively. For unknown-type faults, the accuracy also achieved 100% and 97.5%, respectively.
Keyword ：
Cross-domain fusion multi-scale convolutional autoencoder (CFMS-CAE) Cross-domain fusion multi-scale convolutional autoencoder (CFMS-CAE) Distribution transformer Distribution transformer Mechanical faults Mechanical faults Open-set domain adaptation classifier(OSDA-C) Open-set domain adaptation classifier(OSDA-C) Vibration signals Vibration signals
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| GB/T 7714 | Huang, Haiyan , Gao, Wei , Yang, Gengjie . Distribution transformer mechanical faults diagnosis method incorporating cross-domain feature extraction and recognition of unknown-type faults [J]. | MEASUREMENT , 2024 , 238 . |
| MLA | Huang, Haiyan et al. "Distribution transformer mechanical faults diagnosis method incorporating cross-domain feature extraction and recognition of unknown-type faults" . | MEASUREMENT 238 (2024) . |
| APA | Huang, Haiyan , Gao, Wei , Yang, Gengjie . Distribution transformer mechanical faults diagnosis method incorporating cross-domain feature extraction and recognition of unknown-type faults . | MEASUREMENT , 2024 , 238 . |
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This paper presents a novel approach that simultaneously enables photovoltaic (PV) inversion and flexible arc suppression during single-phase grounding faults. Inverters compensate for ground currents through an arc-elimination function, while outputting a PV direct current (DC) power supply. This method effectively reduces the residual grounding current. To reduce the dependence of the arc-suppression performance on accurate compensation current-injection models, an adaptive fuzzy neural network imitating a sliding mode controller was designed. An online adaptive adjustment law for network parameters was developed, based on the Lyapunov stability theorem, to improve the robustness of the inverter to fault and connection locations. Furthermore, a new arc-suppression control exit strategy is proposed to allow a zerosequence voltage amplitude to quickly and smoothly track a target value by controlling the nonlinear decrease in current and reducing the regulation time. Simulation results showed that the proposed method can effectively achieve fast arc suppression and reduce the fault impact current in single-phase grounding faults. Compared to other methods, the proposed method can generate a lower residual grounding current and maintain good arc-suppression performance under different transition resistances and fault locations.
Keyword ：
Adaptive control Adaptive control Exit strategy Exit strategy Flexible arc suppression Flexible arc suppression Fuzzy neural network Fuzzy neural network Photovoltaic inverter Photovoltaic inverter Sliding mode control Sliding mode control
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| GB/T 7714 | Tang, Junyi , Gao, Wei . A novel cascaded H-bridge photovoltaic inverter with flexible arc suppression function [J]. | GLOBAL ENERGY INTERCONNECTION-CHINA , 2024 , 7 (4) : 513-527 . |
| MLA | Tang, Junyi et al. "A novel cascaded H-bridge photovoltaic inverter with flexible arc suppression function" . | GLOBAL ENERGY INTERCONNECTION-CHINA 7 . 4 (2024) : 513-527 . |
| APA | Tang, Junyi , Gao, Wei . A novel cascaded H-bridge photovoltaic inverter with flexible arc suppression function . | GLOBAL ENERGY INTERCONNECTION-CHINA , 2024 , 7 (4) , 513-527 . |
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Accurate modeling of high-impedance arc fault (HIAF) is of great significance for studying the characteristics of arc fault and suppressing its harm. In traditional arc models, the arc column is usually considered a cylindrical channel with constant length and diameter. However, the arc-burning process is susceptible to the environment. The changes in arc length and diameter present complex characteristics. Therefore, this study proposes a new HIAF model for distribution networks based on the arc's dynamic geometry dimension (DGD). First, the arc length, diameter, and field strength expressions are improved based on the classical cybernetic model. Next, an automatic parameter optimization method for the DGD model is proposed, and then this model is compared with existing advanced models. After that, the effects of the variable parameters of this model on arc characteristics are analyzed. Finally, the practical application effect of this model is tested. The experimental results show that the DGD model can accurately describe the dynamic arc development process, approximate the given arc waveform closely, and generate high-quality samples, which has certain advantages.
Keyword ：
Arc model Arc model Distribution network Distribution network Geometry size Geometry size High-impedance arc fault High-impedance arc fault Model parameter determination Model parameter determination
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| GB/T 7714 | Gao, Wei , He, Wen-Xiu , Wai, Rong-Jong et al. High-impedance arc fault modeling for distribution networks based on dynamic geometry dimension [J]. | ELECTRIC POWER SYSTEMS RESEARCH , 2024 , 229 . |
| MLA | Gao, Wei et al. "High-impedance arc fault modeling for distribution networks based on dynamic geometry dimension" . | ELECTRIC POWER SYSTEMS RESEARCH 229 (2024) . |
| APA | Gao, Wei , He, Wen-Xiu , Wai, Rong-Jong , Zeng, Xiao-Feng , Guo, Mou-Fa . High-impedance arc fault modeling for distribution networks based on dynamic geometry dimension . | ELECTRIC POWER SYSTEMS RESEARCH , 2024 , 229 . |
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To address the low accuracy and stability when applying classical control theory in distribution networks with distributed generation, a control method involving flexible multistate switches (FMSs) is proposed in this study. This approach is based on an improved double-loop recursive fuzzy neural network (DRFNN) sliding mode, which is intended to stably achieve multiterminal power interaction and adaptive arc suppression for single-phase ground faults. First, an improved DRFNN sliding mode control (SMC) method is proposed to overcome the chattering and transient overshoot inherent in the classical SMC and reduce the reliance on a precise mathematical model of the control system. To improve the robustness of the system, an adaptive parameter-adjustment strategy for the DRFNN is designed, where its dynamic mapping capabilities are leveraged to improve the transient compensation control. Additionally, a quasi-continuous second- order sliding mode controller with a calculus-driven sliding mode surface is developed to improve the current monitoring accuracy and enhance the system stability. The stability of the proposed method and the convergence of the network parameters are verified using the Lyapunov theorem. A simulation model of the three-port FMS with its control system is constructed in MATLAB/Simulink. The simulation result confirms the feasibility and effectiveness of the proposed control strategy based on a comparative analysis. © 2024
Keyword ：
Adaptive control systems Adaptive control systems Electric arcs Electric arcs Electric grounding Electric grounding Electric power distribution Electric power distribution Fuzzy inference Fuzzy inference Fuzzy neural networks Fuzzy neural networks MATLAB MATLAB Sliding mode control Sliding mode control System stability System stability
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| GB/T 7714 | Liao, Jianghua , Gao, Wei , Yang, Yan et al. Control method based on DRFNN sliding mode for multifunctional flexible multistate switch [J]. | Global Energy Interconnection , 2024 , 7 (2) : 190-205 . |
| MLA | Liao, Jianghua et al. "Control method based on DRFNN sliding mode for multifunctional flexible multistate switch" . | Global Energy Interconnection 7 . 2 (2024) : 190-205 . |
| APA | Liao, Jianghua , Gao, Wei , Yang, Yan , Yang, Gengjie . Control method based on DRFNN sliding mode for multifunctional flexible multistate switch . | Global Energy Interconnection , 2024 , 7 (2) , 190-205 . |
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