稳健性(进化)
粒子群优化
非线性系统
断层(地质)
控制理论(社会学)
直线(几何图形)
计算机科学
工程类
算法
数学
地质学
基因
地震学
人工智能
量子力学
控制(管理)
几何学
物理
化学
生物化学
作者
Hamid Mirshekali,Rahman Dashti,Hamid Reza Shaker,Reza Samsami,Amin Torabi Jahromi
出处
期刊:IEEE Transactions on Industrial Informatics
[Institute of Electrical and Electronics Engineers]
日期:2021-12-01
卷期号:17 (12): 8308-8318
被引量:28
标识
DOI:10.1109/tii.2021.3067007
摘要
The line parameters of the distribution network (DN) may change because of the atmospheric, structural, and operational conditions. The uncertainty of line parameters can compromise the accuracy of the automatic fault location methods. Besides, arc faults (AFs) may happen in the DN. These faults are difficult to locate in the faulty section because of the nonlinear, asymmetric, and random nature of AF current. In this article, we present a new time-domain fault location (TDFL) method to determine the location of the fault in smart power DN under the line parameters uncertainty. In the suggested method, line parameters' accurate values are determined using a mixed gradient descent particle swarm optimization algorithm. The suggested method's performance is investigated with the help of an IEEE 123-node test feeder in MATLAB (R2018b). The effects of parameter uncertainty, distributed generations operation conditions and modes, different types of AF, various fault distances, resistances, and the fault inception angles are studied. For further evaluation of the proposed method's robustness, two practical tests in the laboratory are carried out. The results confirm that the proposed TDFL method has high accuracy.
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