频率偏差
谐波
S变换
电子工程
时频分析
快速傅里叶变换
计算机科学
闪烁
控制理论(社会学)
工程类
能量(信号处理)
自动频率控制
小波变换
算法
滤波器(信号处理)
电气工程
电信
数学
小波包分解
人工智能
统计
电压
小波
控制(管理)
作者
Chengbin Liang,Zhaosheng Teng,Jianmin Li,Wenxuan Yao,Lei Wang,Qiang He,Shiyan Hu
出处
期刊:IEEE Transactions on Power Delivery
[Institute of Electrical and Electronics Engineers]
日期:2022-08-01
卷期号:37 (4): 2942-2952
被引量:9
标识
DOI:10.1109/tpwrd.2021.3119918
摘要
Renewable energy sources will be more vigorously deployed under the global trend of carbon emission reduction. The connection of numerous renewable energy sources poses an increasingly critical challenge to power quality (PQ) issues in power systems. Time-frequency analysis (TFA) is a foundational technique for real-time monitoring and disturbance detection for power signals. This paper develops an improved S-transform (IST) to accurately detect the disturbances such as oscillatory transient, time-varying harmonics and interharmonics, flicker, swell, sag, interrupt, phase jump, and frequency variation. The proposed IST features the exploration of a designed Gaussian window as the kernel function, whose shape and frequency spectrum can be controlled using a standard deviation based detection frequency parameter. This ensures that the detection requirements at different detection frequencies can be easily met. The IST can be realized by fast Fourier transform (FFT) and its inverse, which ensures that it can be implemented quickly. The IST can accurately detect the amplitude and phase information of fundamental signal, which is beneficial to determine the start and end time, and the intensity of disturbance. With the increase of detection frequency, IST also has excellent energy concentration performance. Simulation and experimental results validated the effectiveness and feasibility of the proposed method.
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