Islanding detection in utility grid with renewable energy using rate of change of frequency and signal processing technique

Q3 Engineering
O. Mahela, Pappu Ram Bheel, M. K. Bhaskar, B. Khan
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引用次数: 2

Abstract

This manuscript has introduced an algorithm based on current signals and frequency rate change (ROCOF) to identify islanding events. Current is analyzed by the use of Stockwell transform (ST) at 3.84 kHz sampling frequency (SF) and a median of absolute values of every column of output matrix (CSIRI) is computed. Rate of change of CSIRI (ROCOCSIRI) is computed. Proposed current based islanding recognition index (IRIC) is computed by multiplying ROCOF with CSIRI & ROCOCSIRI and a weight factor (WC). Threshold values THI1 & THI2 are selected 100 and 3000 for IRIC for identifying the Islanding condition. These are also effective to differentiate islanding conditions from non-islanding events which include both the faulty and operational events. Magnitude of IRIC is greater than 3000 for the faulty events and lower than 100 for operational events. For islanding events magnitude of IRIC falls in between the 100 and 3000. Algorithm is effective to identify and classify the events in three categories which are islanding events, faulty events and operational events effectively. Study is realized in MATLAB/Simulink scenario.
基于频率变化率和信号处理技术的可再生能源电网孤岛检测
本文介绍了一种基于电流信号和频率变化(ROCOF)的孤岛事件识别算法。利用斯托克韦尔变换(ST)分析了3.84 kHz采样频率下的电流,并计算了输出矩阵每列绝对值的中位数。计算了CSIRI (ROCOCSIRI)的变化率。提出的基于电流的孤岛识别指数(IRIC)是通过将ROCOF与CSIRI、ROCOCSIRI和权重因子(WC)相乘来计算的。IRIC选择阈值THI1和THI2分别为100和3000,用于识别孤岛状况。这些也可以有效地区分孤岛条件和非孤岛事件,非孤岛事件包括故障事件和操作事件。故障事件的IRIC值大于3000,运行事件的IRIC值小于100。对于岛屿事件,IRIC的震级在100到3000之间。该算法对孤岛事件、故障事件和运行事件三大类事件进行了有效的识别和分类。研究是在MATLAB/Simulink场景下实现的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
AIMS Electronics and Electrical Engineering
AIMS Electronics and Electrical Engineering Engineering-Control and Systems Engineering
CiteScore
2.40
自引率
0.00%
发文量
19
审稿时长
8 weeks
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