稀疏信号处理在变电站电磁频谱监测中的应用研究

发布时间：2018-06-20 16:00

本文选题：变电站 + 电磁频谱　；参考：《华北电力大学(北京)》2017年硕士论文

【摘要】：随着近几年智能电网的兴起,智能变电站也相伴而生。作为智能电网“电力流、信息流、业务流”三流汇集的焦点,智能变电站对建设坚强智能电网具有极为重要的作用。智能变电站在发挥巨大作用的同时,也暴露出一些亟需解决的问题,例如变电站内一次设备的故障检测问题,二次设备的干扰预警问题以及频谱资源短缺导致的频谱感知问题。研究表明,对变电站进行电磁频谱监测可以有效解决上述问题。然而,现有变电站电磁频谱监测系统存在系统搭建复杂、体积庞大、监测频域过窄以及成本较高等缺陷,难以满足变电站生产现场多点频谱实时监测的需求。为此,本文提出了一种基于稀疏信号处理理论的变电站电磁频谱监测系统。在对稀疏信号处理理论进行了系统的梳理后,本文作者前往东南沿海某城市三所不同电压等级的变电站进行了现场测量,获取了变电站电磁频谱的实际数据,数理统计分析后得出变电站内的电磁频谱具有稀疏性,块稀疏性并且不同地点的电磁频谱具有相关性。针对得到的频谱稀疏特性,本文构建了变电站电磁频谱的联合稀疏模型,即变站内不同地点的频谱不仅包含稀疏支撑集相同的公共部分,还包含单独稀疏部分。进一步地,基于这一稀疏模型以及变电站实际生产中多点实时监测的需求,本文提出了一套使用变电站内无线传感节点进行协作压缩感知从而获得电磁频谱的监测模型。最后,本文提出了一种联合二叉树分解块正交匹配追踪算法用于压缩感知后的信号重构,并通过Matlab仿真验证了所提出算法的优越性。
[Abstract]:With the rise of smart grid in recent years, intelligent substation also comes along. As the focus of "power flow, information flow and business flow" in smart grid, intelligent substation plays an important role in building a strong smart grid. While intelligent substation plays a great role, it also exposes some problems that need to be solved, such as fault detection of primary equipment in substation, interference warning of secondary equipment and spectrum sensing caused by shortage of spectrum resources. The study shows that the electromagnetic spectrum monitoring can effectively solve the above problems. However, the existing substation electromagnetic spectrum monitoring system has some shortcomings, such as complex system construction, large volume, narrow frequency domain and high cost, etc. It is difficult to meet the needs of real-time monitoring of multi-point spectrum in substation production site. In this paper, a transformer substation electromagnetic spectrum monitoring system based on sparse signal processing theory is proposed. After systematically combing the theory of sparse signal processing, the author went to three substations with different voltage levels in a city along the southeast coast to carry out field measurements, and obtained the actual data of the electromagnetic spectrum of the substation. The statistical analysis shows that the electromagnetic spectrum in substation is sparse and block sparse and the electromagnetic spectrum of different locations is correlated. In this paper, a joint sparse model of substation electromagnetic spectrum is constructed, which means that the spectrum of different locations in a transformer substation contains not only a common part with the same sparse support set, but also a separate sparse part. Furthermore, based on this sparse model and the requirement of multi-point real-time monitoring in substation production, a set of monitoring models using wireless sensor nodes in substation for cooperative compression sensing to obtain electromagnetic spectrum is proposed in this paper. Finally, a combined binary tree decomposition block orthogonal matching tracking algorithm is proposed for signal reconstruction after compression and perception, and the superiority of the proposed algorithm is verified by Matlab simulation.
【学位授予单位】：华北电力大学(北京)
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM63;TN911.7

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