Flicker Parameters Detection Technology Based on Improved Energy Operator of Optimized Sampling Interval and MSLD-SCW Function Spectrum Correction in and Its Application in Wind Farms
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摘要: 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。Abstract: With the wide development and application of grid-connected wind power generation and power electronics technologies, the voltage fluctuation and flicker problem can not be ignored in smart grid. Considering the voltage flicker model under rectangular wave modulation which is more sensitive to human eyes, a method for detecting voltage flicker envelope parameters based on improved energy operator and windowed interpolation Fast Fourier Transform (FFT) is proposed. By optimizing the sampling interval of energy operator, the voltage fluctuation components can be accurately extracted. A Maximum Side-Lobe Decay(MSLD) Self-Convolution Window(MSLD-SCW) function with excellent frequency domain performance can be obtained by improved six-term combined cosine window with MSLD, the rectification formula of spectral line interpolation based on new MSLD-SCW is derived, and the detection and analysis of flicker parameters are realized accordingly. The simulation results indicate that the optimization and improvement algorithm can effectively maintain higher detection accuracy than the traditional methods in the case of single frequency rectangular wave modulation, multi-frequency modulation, containing harmonics and sub/supersynchronous inter-harmonics interference, power grid fundamental frequency deviation and noise interference. Finally, the optimization algorithm is applied to voltage flicker envelope parameters detection in a certain area of XinJiang, and the effectiveness of the algorithm is verified.
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