数据压缩方法研究及其在电力系统中的应用

发布时间：2019-02-19 19:27

【摘要】：随着经济的发展和社会的进步，高质量的电能成为电力系统和电力用户的共同需求，这就要求更高效的电能质量检测与分析技术，而这又以电力数据的采集和压缩为基础。近年来，研究人员在电力数据压缩方面进行了各种方法的研究与尝试。传统的有损压缩方法在电力数据量巨大的前提下或多或少会存在数据的损失，往往会丢失信号的关键特征；无损压缩方法能够保持原始信息完整，，但要求较高的硬件条件，占用更多的资源。本文深入研究了压缩感知理论在电能质量数据压缩以及重构中的应用，并引入传统的电能质量无损压缩算法LZW作为对比。压缩感知理论不依赖于Nyquist采样定理，采样率从信号本身的结构和特性出发，远低于传统采样频率，在采集端就将传统的信号采集与压缩两个步骤合二为一，大大减小了数据量的处理。与LZW算法相对比，压缩感知理论在压缩比和重构误差两个指标上面都有不错的表现。首先，本文分类介绍了数据压缩方法的基本原理以及压缩感知理论的研究现状和发展趋势，并且参照IEEE电能质量有关标准以及有关国内外文献对电能质量扰动信号进行了分类，构建了电能质量扰动信号的数学模型。其次，本文阐述了LZW无损压缩算法与压缩感知方法的基本理论，在两种方法的理论基础上分别介绍了信号压缩与重构的实现过程，并且在理论上总结了两种方法的优缺点以及应用的必要条件。最后，本文在电能质量扰动信号数学模型的基础上分别对两种算法进行了仿真实验，并进行了重构性能分析，以压缩效果和重构误差这两个标准对两种方法进行了评价与比较，对压缩感知理论未来的发展方向提出了自己的见解。
[Abstract]:With the development of economy and the progress of society, high quality electric energy becomes the common demand of power system and power users, which requires more efficient power quality detection and analysis technology, which is based on the collection and compression of power data. In recent years, researchers have studied and tried various methods in power data compression. The traditional lossy compression method can lose the data more or less under the premise of the huge power data, and often lose the key features of the signal. Lossless compression method can maintain the integrity of original information, but requires higher hardware conditions and takes up more resources. In this paper, the application of compression sensing theory in power quality data compression and reconstruction is deeply studied, and the traditional power quality lossless compression algorithm, LZW, is introduced as a comparison. Compression sensing theory does not depend on the Nyquist sampling theorem. The sampling rate is far lower than the traditional sampling frequency from the structure and characteristics of the signal itself. At the acquisition end, the two steps of traditional signal acquisition and compression are combined together. The data processing is greatly reduced. Compared with LZW algorithm, compression sensing theory has good performance on compression ratio and reconstruction error. Firstly, this paper introduces the basic principle of data compression method, the research status and development trend of compression sensing theory, and classifies the power quality disturbance signal with reference to the IEEE power quality standards and related literature at home and abroad. The mathematical model of power quality disturbance signal is constructed. Secondly, the basic theory of LZW lossless compression algorithm and compression sensing method is introduced, and the realization process of signal compression and reconstruction is introduced based on the two methods. The advantages and disadvantages of the two methods and the necessary conditions for their application are summarized theoretically. Finally, on the basis of the mathematical model of power quality disturbance signal, two algorithms are simulated, and the reconstruction performance is analyzed. The two methods are evaluated and compared according to the compression effect and the reconstruction error. The author puts forward his own opinion on the future development of the theory of compressed perception.
【学位授予单位】：燕山大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM711

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