Hanning self-convolution window and its application to harmonic analysis

The Hanning self-convolution window (HSCW) is proposed in this paper. And the phase difference correction algorithm based on the discrete spectrum and the HSCW is given. The HSCW has a low peak side lobe level, a high side lobe roll-off rate, and a simple spectrum representation. Hence, leakage errors and harmonic interferences can be considerably reduced by weighting samples with the HSCW, the parameter estimation by the HSCW-based phase difference correction algorithm is free of solving high order equations, and the overall method can be easily implemented in embedded systems. Simulation and application results show that the HSCW-based phase difference correction algorithm can suppress the impacts of fundamental frequency fluctuation and white noise on harmonic parameter estimation, and the HSCW is advantageous over existing combined cosine windows in terms of harmonic analysis performance.

基于能量算子和最大旁瓣衰减自卷积窗函数频谱校正的电压闪变参数识别技术及其在风电场的应用研究

风力发电并网和电力电子技术的广泛发展与应用,造成的电压波动与闪变已成为当前智能电网不容忽视的问题。针对人眼更为敏感的矩形波调制下的电压闪变模型,该文提出改进能量算子和加截断窗谱线插值快速傅里叶变换(FFT)的闪变包络参数识别法。通过优化能量算子采样间隔实现电压波动分量准确提取,以改进的最大旁瓣衰减速率(MSLD)6项组合余弦窗为母窗构建频域性能优良的MSLD自卷积窗(MSLD-SCW)函数,推导基于新型2阶MSLD-SCW函数谱线插值校正公式,据此实现矩形方波调制的闪变参数识别与分析。仿真结果表明,优化改进算法在单频矩形方波调制、多频方波调幅波调制、含有谐波与次/超同步间谐波干扰、基频变动及含有噪声等干扰源背景下,相较于传统检测算法均保持较高准确性。最后,将优化算法应用于新疆某地区电网电压闪变识别,验证其有效性。