故障检测与隔离
断层(地质)
分布式发电
计算机科学
可靠性(半导体)
灵敏度(控制系统)
故障指示器
能量(信号处理)
工程类
可靠性工程
功率(物理)
人工智能
电子工程
可再生能源
统计
电气工程
物理
地质学
量子力学
地震学
执行机构
数学
作者
Gustavo G. Santos,Thiago S. Menezes,Pedro Henrique Aquino Barra,José Carlos de Melo Vieira Júnior
标识
DOI:10.1016/j.ijepes.2021.107663
摘要
As support to fault location algorithms, this paper presents a new method for detecting and classifying faults in active distribution networks using the energy moving averages of the current signals measured at the feeder head. A proposal for updating the energy thresholds for fault detection is introduced, aiming to achieve higher sensitivity in fault detection, especially for scenarios with high penetration levels of distributed generation (DG). Since the power injected by DG can rapidly change, this proposal is essential for maintaining the fault detection method's reliability. Also, the fault classification is based on an analytical approach, making it possible to be easily applied to different operating scenarios of a distribution system. Thus, its potential for real-world implementation is higher when compared to classifiers based on supervised learning algorithms. Performance tests on the IEEE 34-node test feeder showed that this method is reliable for detecting and classifying different fault types, with diverse generation-load scenarios and noisy signals.
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