| 引用本文: | 李振兴,张星宇,朱 益,等.基于U-I象空间分布的CT饱和识别及畸变电流重构方法[J].电力系统保护与控制,2026,54(02):1-12.[点击复制] |
| LI Zhenxing,ZHANG Xingyu,ZHU Yi,et al.CT saturation identification and distorted current reconstruction method based on U-I image spatial distribution[J].Power System Protection and Control,2026,54(02):1-12[点击复制] |
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| 基于U-I象空间分布的CT饱和识别及畸变电流重构方法 |
| 李振兴1,2,张星宇1,朱益1,翁汉琍1,2,李振华1,2,周吉安1 |
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| (1.三峡大学电气与新能源学院，湖北 宜昌 443002;2.新能源微电网湖北省
协同创新中心(三峡大学)，湖北 宜昌 443002) |
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| 摘要: |
| 电流互感器(current transformer, CT)是各类差动保护的核心元件，但在复杂故障电流特性及幅值显著提升的工况下极易发生饱和。首先，融合测点处电压互感器(potential transformer, PT)提供的电压量信息，通过建立电压-电流耦合关系在二维象空间中绘制以电流量为横轴、电压量为纵轴的轨迹曲线，从而抑制CT饱和导致的单一信号失真对状态辨识的干扰。基于轨迹畸变程度与标准椭圆的量化偏差，实现饱和状态的识别及严重程度的分级评估。最后，在线性传变区间内筛选采样点并结合改进的椭圆拟合算法完成象空间分布的整合及畸变电流的重构。在PSCAD/EMTDC平台搭建220 kV输电线路模型及新能源电源接入模型，仿真结果显示，在CT不同饱和类型及严重程度下，所提方法能高效、精确地实现CT饱和状态识别及二次畸变电流的重构。 |
| 关键词: 电流互感器 饱和识别 线性传变 椭圆拟合算法 电流重构 |
| DOI：10.19783/j.cnki.pspc.250231 |
| 投稿时间：2025-03-06修订日期：2025-06-03 |
| 基金项目:国家自然科学基金项目资助(52077120) |
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| CT saturation identification and distorted current reconstruction method based on U-I image spatial distribution |
| LI Zhenxing1,2,ZHANG Xingyu1,ZHU Yi1,WENG Hanli1,2,LI Zhenhua1,2,ZHOU Ji’an1 |
| (1. College of Electrical and New Energy, China Three Gorges University, Yichang 443002, China; 2. Hubei Provincial
Collaborative Innovation Center for New Energy Microgrid, China Three Gorges University, Yichang 443002, China) |
| Abstract: |
| Current transformers (CTs) are core components of various differential protection, but they are prone to saturation under complex fault current characteristics and significantly increased current amplitudes. First, voltage information provided by potential transformers (PTs) at measurement points is integrated, and a voltage-current coupling relationship is established to plot trajectory curves in a two-dimensional image space, with current on the horizontal axis and voltage on the vertical axis. This approach mitigates the interference of single-signal distortion caused by CT saturation on state identification. Based on the deviation of the degree of trajectory from a standard ellipse, saturation states are identified and the severity of saturation is graded. Finally, sampling points within the linear transmission interval are selected, and an improved ellipse-fitting algorithm is applied to integrate the image space and reconstruct the distortion current. A 220 kV transmission line model with new energy integration is constructed on the PSCAD/EMTDC platform. Simulation results show that the proposed method can efficiently and accurately identify CT saturation and reconstruct secondary distorted currents under different types and severities of CT saturation. |
| Key words: current transformer saturation recognition linear transmission ellipse-fitting algorithm current reconstruction |
