智能电表总谐波失真检测与估计的优化技术

Eakchai Junput, Sathit Chantree, M. Leelajindakrairerk, C. Chompoo-Inwai
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引用次数: 8

摘要

本文提出了一种基于快速傅立叶变换(FFT)方法的智能电表总谐波失真检测与估计的优化技术。设计考虑了恒频和非恒频包括不平衡电压的精度,以提高效率和减轻谐波失真值。实验结果表明,该算法能够准确地检测出总谐波失真,最大误差为0.058%。然而,通常情况下,总谐波失真估计的准确性取决于输入信号的采样率。准确、快速地分析信号是智能电表最重要的操作关键。因此,本文的目标是在12.8 kHz和25.6 kHz之间寻找最佳采样率。结果表明,最佳采样频率为12.8 kHz。因为%THD值的结果在每种情况下都很接近,但在采样率12.8 kHz时,使用的计算时间比减少内存使用和处理时间少。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal technique for total harmonic distortion detection and estimation for smart meter
This paper proposes an optimal technique for total harmonics distortion detection and estimation for smart meter by applying Fast Fourier Transform (FFT) methodology to detect harmonic distortion. Design considers the precision of constant frequency and inconstant frequent including unbalance voltage in order to enhance efficiency and mitigate harmonic distortion value. These results show that implemented algorithm can detect total harmonic distortion precisely with maximum 0.058% error. However, usually, the accurate of Total Harmonic Distortion estimation will depend on the sampling rate of input signal. The most significant operating key of the Smart Meter is to accurately and rapidly analyses the signal. Therefore, this paper aims to find optimum sampling rate between 12.8 kHz and 25.6 kHz. From the result, the optimum sampling is 12.8 kHz. Because result of %THD value we're close in every cases but at sampling rate 12.8 kHz used in less computation time than to reduce memory use and processing time.
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