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光伏发电技术 故障诊断 ★ 5.0

基于反射法的光伏系统故障检测统计分析

A Statistical Analysis of Fault Detection in Photovoltaics Using Reflectometry

作者 Ayobami S. Edun · Cody LaFlamme · Evan J. Benoit · Cynthia Furse · Joel B. Harley
期刊 IEEE Journal of Photovoltaics
出版日期 2025年9月
技术分类 光伏发电技术
技术标签 故障诊断
相关度评分 ★★★★★ 5.0 / 5.0
关键词 扩频时域反射仪 故障检测 光伏阵列 检测概率 环境与系统变化
语言:

中文摘要

扩频时域反射法(SSTDR)已被用于检测电缆、飞机布线和光伏(PV)装置中的各类故障。一个显著的问题是,由于大多数使用反射法的方法都基于与已知基线的比较,系统或环境变化导致的基线变化可能会掩盖故障产生的反射信号,从而降低检测概率。对于远离测试设备的故障,这些变化的影响会更加严重。本研究的目的是在环境变化、系统变化以及线路不同位置的情况下,通过统计方法估算光伏阵列反射信号是否为故障的概率。我们的研究结果展示了在不同信噪比(SNR)条件下,当出现部分断开和完全断开故障时,在距离测试设备不同距离处检测到故障的概率。在距离测试仪97.54米(320英尺)处,当信噪比约为9 dB时,检测到完全断开故障的概率高达0.75,而在同一位置检测部分故障的概率几乎为零。我们还给出了无法再检测到故障的情形,以及平均法如何有助于提高检测概率。

English Abstract

Spread spectrum time domain reflectometry (SSTDR) has been used to detect different kinds of faults in cables, aircraft wiring, and photovoltaic (PV) setups. One significant problem is that, since most methods that use reflectometry are based on a comparison with a known baseline, variations in the baseline caused by system or environmental variations can overshadow the reflections produced by faults and reduce the probability of detection. The effects of these variations are exacerbated for faults far from the test device. The objective of this work is to statistically estimate the probability that a reflection from a PV array is or is not a fault amid environmental variations, system variations, and at different locations along the line. Our results show the probability of detecting fault presence at different distances from the test device when there are partial and full disconnects over a range of signal-to-noise ratio (SNR). At a distance of 97.54 m (320 ft) from the tester, the probability of detection of a full disconnect is as high as 0.75 with an SNR of about 9 dB, while the probability of detection is nearly zero for partial faults at the same location. We also present scenarios where faults can no longer be detected and how averaging could help improve the probability of detection.
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SunView 深度解读

该SSTDR故障检测技术对阳光电源SG系列光伏逆变器及iSolarCloud智能运维平台具有重要应用价值。技术可集成至逆变器直流侧输入端,实现对组串高阻连接、断路及短路故障的在线监测,弥补传统IV曲线诊断对隐性故障识别不足的缺陷。其抗噪声能力强的特性适配复杂电磁环境下的大型地面电站应用。建议将反射法信号特征融入iSolarCloud预测性维护算法,结合MPPT异常波动数据实现早期故障预警,降低电弧火灾风险,提升1500V高压系统安全性。该方法可扩展至PowerTitan储能系统电池簇连接故障诊断,形成统一的直流侧健康管理方案。