可观测性
可控性
断层(地质)
智能电网
计算机科学
故障检测与隔离
网格
电力系统
执行机构
可靠性工程
数据挖掘
工程类
人工智能
功率(物理)
电气工程
数学
几何学
应用数学
地震学
地质学
量子力学
物理
作者
Paschalia Stefanidou-Voziki,Nikolaos Sapountzoglou,Bertrand Raison,José Luís Domínguez‐García
标识
DOI:10.1016/j.epsr.2022.108031
摘要
The evolution of the conventional power systems to smart grids has changed the way to conceive and operate them. The part of the grid evolving the most is the distribution grid where the installation of additional sensors and actuators has increased its observability and controllability. These have enabled the development of more accurate and automated processes including some critical ones such as the fault detection, isolation and restoration techniques. In this direction, unconventional methods, e.g. artificial intelligence, have been increasing in popularity over the last years. In this paper, fault location and fault classification methods are reviewed for both medium–voltage and the until recently unexplored case of low–voltage distribution grids. Different methods applied for both fault location and fault classification are being classified by the implemented technique. Such methods are explained and analyzed providing the main advantages and disadvantages of each category. Additionally, the research trends in both fields are analyzed and state–of–the–art methods from each category are thoroughly compared. Finally, the research gaps are identified.
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