电力系统论文：电力系统低频振荡在线分析方法研究.doc

电力系统论文：电力系统低频振荡在线分析方法研究【中文摘要】随着我国“西电东送、南北互供、全国联网、厂网分开”电力政策的实施,区域间的联网规模逐步扩大,加之高放大倍数快速励磁系统的广泛应用,进一步恶化了系统阻尼,在扰动情况下极易引发低频振荡问题,严重威胁到电网的安全稳定运行,是提高外送能力的重要瓶颈。低频振荡分析是低频振荡研究的重要内容,也是开展抑制低频振荡研究的基础。特征值分析法是研究电力系统低频振荡问题的基本方法,但其分析结果的可靠度依赖于数学模型的准确程度,因此不依赖于数学模型的在线分析方法对大互联系统更具现实意义。Prony方法和HHT方法是目前研究较多的两种低频振荡在线分析方法,基于指数函数拟合思想的Prony算法是一种能够根据采样值直接估算给定信号的幅值、频率、衰减因子和初相角的分析方法。HHT方法由经验模态分解EMD和Hilbert变换两部分组成,其核心部分是EMD。EMD是把信号中不同尺度的波动或趋势逐级分解开来,产生一系列具有不同特征尺度的数据序列的过程,由此可以对非线性、非平稳的数据进行线性和平稳化处理,得到能反应原信号局部特征的IMF分量。本文研究了Prony方法和HHT方法两种分析方法,并通过仿真算例对比分析了两种方法的优缺点。Prony方法理论完善,物理意义明确,分析结果准确,但对噪声敏感。HHT方法具有自适应滤波特性,不需要去直、滤波等数据预处理,但存在模态混淆和端点效应等问题。针对含噪声的采样数据,本文提出一种综合EMD和Prony的低频振荡在线分析方法。首先对复杂含噪信号进行EMD分解,得到单一尺度的IMF分量；然后判断并分离IMF分量中的噪声成分,做数据重构；最后采用Prony方法对重构信号进行分析,实现对含噪声采样信号的低频振荡在线辨识。仿真结果表明,该方法是准确可行的,对电力系统低频振荡在线分析具有实用价值。【英文摘要】As the policy of “west-to-east electricity transmission, north-south supply for each other, nation-wide power grid interconnection, the separation of power plant and supplement” implementing, the capacity of grid gradually enlarging, addition of the fast high magnification excitation system applying, further deteriorating of the system damping. Therefore, the low-frequency oscillations problems are easy caused by a small disturbance, seriously threaten the safe stable operation of the grid, which is an important bottleneck for power outgoing capacity.Low-frequency oscillation analysis is an important part of low-frequency oscillation study, as to the basis of carried out inhibition study to low-frequency oscillation. Eigenvalue analysis the basic methods for low-frequency oscillation study, but its reliability depends on the accuracy of mathematical model, so the online analysis methods which dont depend on systems mathematical model are more realistic for large interconnected system.Prony method and Hilbert-Huang Transform method (HHT method for short) are two main methods for online identification of the power system low-frequency oscillation at present. Prony method basing on the thinking of exponential function fitting can directly estimate the amplitude, frequency, attenuation factor, and initial phase of signal according to sampling value. HHT method is made up of Empirical Mode Decomposition (EMD for short) and hilbert transformat, its core part is EMD. EMD is a process that separates fluctuations or trends with different scales from a signal, producing a series of data with different characteristic scales, therefore, it can realize linearization and smoothing process for non-linear non-stationary signal, getting to the Intrinsic Mode Function(IMF for short) component reflecting the original signals local characteristics. The paper studies Prony method and HHT method, their advantages and disadvantages are comparably analyzed through simulation examples. The Prony method has perfect theory, clear physical significance, accurate results, but it is sensitive to noise. The HHT method with adaptive filtering properties, do not need to go straight, filtering and other data preprocessing, but it has end effection, modes confusion and other problems.For sampling data with noise, the paper presents an online identification method combining the EMD and Prony to analyze the low-frequency oscillations. First,decompose the complex signal with noise, get to IMF components with single scale; then, judge and separate noise components from these IMF components, do data reconstruction;last, analyze the reconstructing signal using Prony method, realize online low-frequency oscillation identification for sampling data with noise. Simulation results show that the comprehensive method is feasible and accurate, and has practical significance to the low-frequency oscillation online analysis.【关键词】电力系统 低频振荡 Prony方法 HHT方法 EMD【英文关键词】Power system Low-frequency oscillations Prony method HHT method EMD【目录】电力系统低频振荡在线分析方法研究摘要6-7Abstract7-8第1章 绪论11-201.1 电力系统低频振荡概述11-121.1.1 引言111.1.2 低频振荡的定义11-121.2 低频振荡的机理12-141.3 低频振荡的分析方法14-171.3.1 特征值分析法14-151.3.2 非线性理论分析法151.3.3 实验分析法15-171.4 低频振荡的抑制措施17-191.5 本文的主要研究内容19-20第2章 Prony方法的原理与应用20-322.1 Prony方法原理20-222.2 Prony方法参数选择22-232.2.1 采样频率的选取222.2.2 时间长度的选取222.2.3 模型有效阶数的确定22-232.3 Prony方法算例分析23-312.3.1 假设的理想信号23-252.3.2 带噪声信号25-282.3.3 4机11节点系统28-302.3.4 3机9节点系统30-312.4 本章小结31-32第3章 HHT变换的原理与应用32-443.1 HHT变换原理32-343.1.1 EMD分解32-343.1.2 Hilbert变换343.2 HHT方法算例分析34-433.2.1 理想信号34-383.2.2 带噪声的信号38-403.2.3 4机11节点系统40-423.2