【作者】 宋雪雷；

【导师】 佟为明；

【作者基本信息】 哈尔滨工业大学 ， 电机与电器， 2007， 博士

【摘要】 近年来电能质量问题已引起人们广泛关注。这主要是因为:一方面,大量非线性、波动性、冲击性和不平衡性负荷的广泛使用导致电能质量日益下降;另一方面,以计算机和微处理器为核心的对电能质量扰动敏感的高自动化和高智能化的电子设备和精密工业对电能质量提出了越来越高的要求。电力系统供电的电能质量是电力工业产品的重要指标,涉及发电、供电、用电各方面的利益。电能质量指标若偏离正常水平过大,会给发电、输电、变电、配电和用电带来不同程度的危害。因此,电能质量问题已经成为电能供应市场的核心问题之一,电能质量检测与分析技术和电能质量控制技术亦成为电力系统领域中新的研究热点。电能质量检测与分析是电能质量控制的基础,建立电能质量监测与分析系统并对电能质量扰动进行正确检测、评估和分类均是十分必要的。本文深入研究了基于复小波变换的动态电能质量扰动检测与定位方法、基于支持向量机的动态电能质量扰动自动识别方法和基于提升小波变换的电能质量扰动数据压缩方法。其应用可提高电能质量监测与分析系统的准确性、实时性及智能化、自动化和网络化水平。为解决常用正交实小波变换不能提取信号相位信息的缺陷,在分析小波相频特性对小波分析效果影响的基础上,提出利用复小波变换的复合信息对动态电能质量扰动进行分析可获得更好的分析效果。由于现有的复小波均为连续小波,为克服其计算复杂等缺陷,深入研究了一种通过改变相频特性由现有正交紧支实小波构造正交紧支复小波的方法。该方法基于多分辨率分析思想,仅要求正交紧支实小波具有低通滤波器即可,由该方法构造的正交紧支复小波具有正交性和紧支性,仍可采用Mallat快速算法。选择Db4正交紧支实小波构造出一种Db4正交紧支复小波,并将其用于动态电能质量扰动检测与定位。所构建的Db4正交紧支复小波滤波器组与原Db4正交紧支实小波滤波器组的长度相同,支集相同,同时具有与Db4正交紧支小波相同的特性:正交性、紧支性、消失矩和正则性。通过仿真,对Db4正交紧支复小波变换与Db4正交紧支实小波变换的分析效果和Db4正交紧支复小波的复合信息与简单信息的分析效果进行了对比分析。鉴于小波变换优秀的时频局部化特性和支持向量机优秀的统计学习能力,提出一种基于复小波变换和多类支持向量机分类器的动态电能质量扰动识别与分类方法:复小波变换主要用于提取动态电能质量扰动的特征向量;多类支持向量机分类器主要用于根据提取的特征向量对动态电能质量扰动进行识别与分类。为克服现有多类支持向量机分类器算法本身存在的一些缺陷,在借鉴模糊聚类分析思想的基础上,提出一种新的多类SVM分类器算法,即分级聚类SVM算法,同时构造了一种基于分级聚类SVM算法的动态电能质量扰动分类树。为验证所提出方法的正确性和有效性,对基于复小波变换和多类支持向量机分类器的动态电能质量扰动识别与分类方法和基于人工神经网络的分类方法进行了对比分析,同时也对分级聚类SVM算法和常用的几种多类SVM分类器算法进行了对比分析。为减少电能质量扰动数据的存储空间、传输数据量以及提高电能质量监测与分析系统的实时性,在深入研究提升小波变换基本理论的基础上,给出一种基于提升小波变换的电能质量扰动数据压缩方法:首先通过提升小波变换对电能质量扰动信号进行多尺度分解;然后根据相应的施加阈值策略对每个尺度上的高频系数进行阈值量化与编码处理,并保存与扰动相关的系数值而抛弃其它与扰动无关的系数值,从而实现电能质量扰动数据压缩;最后可利用提升小波逆变换由压缩后的数据对原始电能质量扰动信号进行重构。在阈值量化与编码步骤采取各个尺度下使用不同软阈值的策略,阈值估计采用极大极小阈值算法。为了更好地验证基于提升小波变换的电能质量扰动数据压缩方法的正确性和有效性,给出了四个数据压缩性能评价指标,并选用Db4正交紧支实小波的提升算法对几种常见电能质量扰动的数据压缩效果进行了仿真测试。设计了一种基于电能质量监测与分析系统,其主站由工控机和PCI CAN板卡构成,从站即为各个电能质量监测装置。同时给出了基于复小波变换和支持向量机的电能质量分析方法在该系统中的软件实现流程。提出一种基于DSP+双口RAM+ARM的电能质量监测装置的硬件设计方案,DSP主要用于电力信号采集、基本电力参数计算、电能质量参数计算与分析,此外还要实现事件记录、故障报警、遥信/遥控等功能;ARM主要用于实现本地显示、CAN通信、系统参数设置、键盘操作等;DSP和ARM之间通过双口RAM进行数据交换。为解决ARM和CAN控制器之间地址与数据总线复用问题,设计了ARM与CAN控制器之间的接口时序电路,该时序电路通过CPLD实现;为提高系统的实时性、稳定性和可靠性,采用了嵌入式实时操作系统μC/OS-II用于ARM软件开发。更多还原

【Abstract】 In recent years, power quality problem have drawn extensive attention of people. One reason is that power quality has been being disturbed heavily with the increasing number of polluting loads such as non-linear loads, time-variant loads, fluctuating loads, unbalanced loads, etc.; the other is that intelligent electrical devices have put forward more rigorous requirements for power quality. As an important index of the power industry product, power quality concerns the interests of generating power, supplying power and utilizing power. In the event that the power quality index departs the normal level too much, it will endanger the electric power generation, electric power transmission, electric power transform, electric power distribution and electric power consumption to a different extent. Therefore, power quality has become one of the primary problems in the electric power market. Power quality monitroing and analysis technology and power quality control technology have become new researching focuses of the electric power system field. Power Quality monitoring and analysis is the basis and premise of power quality control. Therefore, it is very necessary to build a power quality monitoring and analysis system to examine, evaluate and classify the power quality disturbances correctly. This dissertation makes a deep research on methods with regard to power quality analysis which include detection and location method of dynamic power quality disturbances based on complex wavelet transform, automatic recognition and classification method of dynamic power quality disturbances based on multi-class support vector machine classifier; data compression method of power quality disturbances based on lifting wavelet transform. Application of these methods may improve the power quality monitoring and analysis system in aspects of accuracy, real-time performance, automation, etc.In order to resolve the disadvantage of the common-used orthogonal real wavelet transform that it cannot draw the signal’s phase information, based on analyzing the impact of wavelets’phase-frequency characteristic on wavelet analyzing results, it is brought forward that analyzing power quality disturbances by use of compound information of the complex wavelet transform may acquire better analysis results. Since the existing complex wavelets are all continuous wavelets, in order to overcome the disadvantages of complex calculation, this dissertation deeply researches a method for constituting orthogonal compact support complex wavelets by the existing orthogonal compact support real wavelets through changing the phase-frequency characteristic. This method is based on multi-resolution analysis and as long as the orthogonal compact support real wavelet has low-pass filter, it will meet the requirements of this method. Since the orthogonal compact support complex wavelet constituted by means of this method is orthogonal and compact supported, it can adopt Mallat fast wavelet algorithm. In order to acquire much better analysis results, Db4 orthogonal compact support real wavelet is chosen here to constitute a kind of db4 orthogonal compact support complex wavelet,which is used to detect and locate dynamic power quality disturbances. The Db4 orthogonal compact support complex wavelet filter group constituted by means of this method has the same length and the same support set as the original Db4 orthogonal compact support real wavelet. It also has the same characters as the Db4 orthogonal compact support real wavelet , respectively orthogonal, compact support, vanishing moment and regularity. Through simulation, the analysis results of Db4 orthogonal compact support complex wavelet are compared with that of Db4 orthogonal compact support real wavelet, and the analysis results of compound information of orthogonal compact support complex wavelet are compared with that of simple information.Whereas wavelet transform has the excellent characteristic of time-frequency localization, and support vector machine (SVM) has the excellent ability of statistic study, this dissertation brings forward a new method based on complex wavelet transform and multi-class SVM classifier for recognizing and classifying dynamic power quality disturbances. The complex wavelet transform is used to to extract the feature vector of dynamic power quality disturbances, and the multi-class SVM classifier is used to recognize and classify dynamic power quality disturbances according to the feature vector extracted. Based on the theory of structural risk minimization, SVM has stronger generalization ability, and can resolves several deficiencies of artificial neural network. In order to overcome the deficiencies of current multi-class SVM classifier algorithms, this dissertation brings forward a new multi-class SVM classifier algorithm based on fuzzy clustering analysis thought, i.e. hierarchical clustering SVM algorithm,and simultaneously constructs a classification tree for dynamic power quality disturbances based on hierarchical clustering SVM classifier algorithm. The hierarchical clustering SVM algorithm has the merits such as higher learning speed, lower error classification rate, less sub-classifier number, and requiring less memory, etc. In order to certify the correctness and validity of this method, through simulation this dissertation compares the recognition and classification method of dynamic power quality disturbances based on complex wavelet transform and multi-class SVM classifier with that based on artificial neural network, and also compares the hierarchical clustering SVM algorithm with several common-used multi-class SVM classifier algorithm.In order to reduce the storage space and the transmission time of power quality disturbance data, and also in order to enhance the real-time performance of the power quality monitoring and analysis system, this dissertation brings forward a new data compression method of power quality disturbance based on lifting wavelet transform which is as follows: firstly confirm the decomposition scale and make multi-scale decomposition to power quality disturbance signal by lifting wavelet transform; secondly, according to the relevant threshold strategy, make the threshold quantization and encoding operation to the higher frequency coefficients of each scale, and simultaneously store the coefficients with connection to the disturbance and throw away the coefficients without connection to the disturbance, and in this way compression of power quality disturbance data is accomplished; finally according to the compressed data reconstruct the original power quality disturbance signal by use of inverse lifting wavelet transform. In order to evaluate the correctness and validity of the compression method based on lifting wavelet transform, four evaluation indexes of data compression performance, respectively compression ratio, mean square deviation percentage, signal-to-noise ratio and energy ratio, are introduced,. In addition, the lifting algorithm of Db4 orthogonal compact support real wavelet is chosen to make simulation experiments to the compression results of power quality disturbances. This dissertation designs a power quality monitoring and analysis system. The main station is composed of industrial computer and PCI CAN card, and the slave station is just the power quality monitoring device. In addition, the software implementation procedure of power quality analysis method based on complex wavelet transform and SVM in the system is proposed. This dissertation brings forward a hardware scheme for the power quality monitoring device which is based on the DSP+DARAM+ARM structure. DSP is mainly used to gather power signals, calculate basic power parameters, calculate and analyze the power quality parameters, and implement the functions of event recording, malfunction alarming and remote signalling/remote control; ARM is mainly used to implement local display, CAN communication, setting up system parameters and keyboard operation, etc.; DSP and ARM change the data via DARAM. In order to resolve the problem of address bus and data bus multiplexing between ARM and CAN controller, a sequence circuit between ARM and CAN controller, which is implemented via CPLD, is designed. In order to increase the real-time performance, stability and reliability of device, the embedded real-time operation systemμC/OS-II is adopted in ARM software development.更多还原