基于分布式压缩感知的智能用电网络高分辨率谐波与间谐波测量

High-resolution harmonic and interharmonic measurement in smart power utilization network based on distributed compressed sensing

安全可靠的电能质量是智能用电网络的基本需求,谐波与间谐波则是其中最常见的电能质量扰动之一,在智能用电网络中准确的测量分析谐波和间谐波,对于保障用电设备安全具有重要意义。本文提出了一种基于分布式压缩感知的智能用电网络谐波与间谐波测量方法,首先通过构建多通道谐波与间谐波测量模型,将高分辨率的频率估计问题转化为分布式压缩感知中的多测量向量稀疏重构问题,然后利用智能用电网络下各用户谐波与间谐波信号可联合稀疏表示的特性,在不延长观测窗长的前提下,提高了频率估计的准确度,提升了智能用电网络下的抗噪声干扰能力,最终达到准确分析谐波与间谐波的目的。实验结果表明,相较现有的谐波分析参数及非参数方法,本方法在谐波与间谐波测量的准确度和对噪声的鲁棒性上都有相应的提升,为智能用电网络中电能质量的治理提供了有效的参考依据。

Harmonic and interharmonic analysis plays a significant role in smart power utilization network. To realize reliable and accurate harmonic and interharmonic measurement in smart power utilization network,this paper proposes a harmonic and interharmonic measurement method based on distributed compressed sensing in smart power utilization network. Firstly,through constructing multichannel harmonic and interharmonic measurement model,the multi-channel high-resolution frequency estimation problem is translated into the sparse reconstruction problem of the multiple measurement vectors in distributed compressed sensing（ DCS）. Combining with the joint sparsity of multiple harmonic and interharmonic signals of multi-users in the smart power utilization network,the method enhances the frequency estimation accuracy and improves the anti-noise interference ability without lengthening the observation window length. Finally,the goal of accurately analyzing harmonic and interharmonic is achieved. The simulation and actual experiment results demonstrate that compared with existing parametric and non-parametric methods in harmonic and interharmonic analysis of power quality,the proposed method greatly improve the accuracy of harmonic and interharmonic measurement and the robustness to noise,and provides an effective reference basis for controlling and improving the power quality in smart power utilization network.