非线性负载下逆变器并联系统控制策略研究

微电网并联逆变器接入非线性负载时出现的谐波电流,会引起逆变器输出电压畸变严重.以两逆变器并联运行模型为研究对象,提出一种综合控制策略.首先,在电压外环采用比例积分控制和重复控制串联控制方法的同时,考虑下垂控制所引起的基波频率偏移会进一步恶化输出电压质量,改进重复控制方法,实现在频率变化时对电压谐波的有效抑制.其次,由于SOGI可以抑制输入信号的谐波,将基于SOGI的虚拟复阻抗引入到电流反馈环,抑制谐波电流对虚拟复阻抗影响,有效改善功率均分效果和抑制逆变器间环流.最后,对所提出的综合控制策略进行仿真研究,验证所提控制策略的正确性和可行性.     

APF的谐波电流补偿控制策略研究

用电负荷类型的增多及电力电子器件的广泛应用,使得电路中的非线性负载越来越多。这就造成了电网中产生了大量谐波源和功率损耗,给人们生产生活带来了很多的不便。为了更有效地解决电网中的谐波问题,提出了通过采用有源电力滤波器来补偿谐波电流的控制策略。该控制策略基于d-q坐标系,对谐波电流进行检测。采用PI-重复控制方法来实现无静差指定次谐波补偿,以消除谐波电流。将该控制方法与传统的PI控制进行比较,并分析了PI-重复控制方法的动态性能及稳态性能。仿真结果对比证明了PI-重复控制能很好地对谐波电流进行抑制。PI-重复控制作为一种便捷的控制策略,对谐波具有明显的消除作用,能很好地应用到生产、生活中。     

低开关频率下永磁同步电机弱磁区电流谐波抑制

针对内嵌式永磁同步电机在低开关频率下高速深度弱磁区电流畸变、转矩波动大等问题,分析了电机常规控制下系统对扰动信号的抑制作用;常规SVPWM过调制运行时会产生周期性扰动,结合试验及仿真数据,提出采用特定谐波消除SHEPWM调制抑制电流谐波的控制策略,改善了电机平稳运行能力。对所提出的优化脉冲模式进行Matlab仿真和试验验证,结果表明:采用特定谐波消除SHEPWM调制模式,可以有效抑制电机高速弱磁区的电流谐波,改善了系统稳态转矩控制效果。     

基于特征谐波电流的高压直流输电控制策略

为了降低特征谐波电流对高压直流输电产生的危害，提出基于特征谐波电流的高压直流输电控制策略。根据高压直流输电网络的组成元素以及空间分布方式，构建高压直流输电网络模型。在该模型下，利用智能电流表获取实时电流数据，提取高压直流输电电流特征。通过特征匹配识别初始数据中的特征谐波电流，计算特征谐波电流量，求解直流输电电流控制量。将控制量求解结果代入到装设的输电控制器中，从谐波电流抑制、电流裕度补偿和电流限幅等方面完成高压直流输电控制。通过测试实验得出结论：在优化设计高压直流输电控制策略的作用下，特征谐波电流畸变率为0.466%,输电电流的空间不稳定系数为0.23,均满足预设要求。     

基于EPLS的电力系统谐波源的识别与定位

在电力供电优化控制的研究中,谐波是影响电能质量的重要因素,对谐波进行监测和分析具有重要的意义。为定量识别谐波源,准确估算系统谐波阻抗,提出了一种应用加强的偏最小二乘回归(EPLS)的谐波源识别算法,利用EPLS来估算系统谐波阻抗,并识别系统和用户各自所要承担的责任,达到识别谐波源定位目的;通过与二元线性回归、稳健回归以及偏最小二乘算法的比对表明,EPLS算法具有实现简单,分析精度高的优势。通过在MATLAB/SIMULINK中构建仿真模型,应用改进方法进行仿真分析,结果证明了所提方法的正确性和可行性。     

电动汽车充电桩谐波放大效应研究

电动汽车充电桩运行时产生的谐波,在采用并联APF(active power filter)治理时,负载侧会产生谐波放大效应。该文提出改进APF检测跟踪策略,通过改进ip-iq检测与双重准谐振控制来精确补偿5、7次谐波,降低了谐波补偿率和改进APF拓扑结构,通过在负载侧并联无源滤波器,增大负载交流侧阻抗,两个方面来抑制充电桩负载侧谐波放大效应。仿真结果证明了改进方法的正确性。     

高阶统计量方法在谐波恢复中的应用

谐波恢复是信号处理中的重要问题,谐波恢复就是在噪声中分析组成信号的各次谐波.噪声分为加性噪声和乘性噪声,本文分析加性噪声和乘性噪声的特点,提出采用高阶统计量的方法抑制噪声,恢复谐波.通过四阶统计量的切片抑制乘性噪声,采用二阶累积量谱抑制加性噪声.仿真结果表明,本方法具有很好的抑制噪声效果.     

基于DSP的电力谐波发生器设计

基于DSP的电力谐波发生器,具有输出所含谐波次数可设置、谐波含量可调、谐波注入时间可控、动态响应时间快等特点。为了实现对多个不同频率的交流信号的无静差跟踪,采用改进型重复控制策略。在MATLAB/Simulink中搭建系统模型,进行仿真。并采用基于模型设计的方法,自动生成代码,克服了电力电子装置传统开发模式中研发周期长,代码测试及验证费时费力等缺点。最终,在3 kW的样机上进行了实验。实验结果表明,电力谐波发生器输出电压的误差精度小于3%,可满足测试电气设备性能的要求。     

基于稳健回归的系统谐波阻抗及用户谐波发射水平的估计方法

该文提出了一种基于稳健回归的系统谐波阻抗及用户谐波发射水平的评估方法,即通过对系统公共连接点的同步测量,获取系统中谐波电流、电压信号,并利用复加权最小二乘迭代法计算出谐波回归系数;然后以上次迭代残差函数作为权重,并将Huber函数当做影响函数,进行加权迭代计算,这样能够避免或减少回归系数受奇异值的影响;系统谐波阻抗有回归系数映射出,同时对用户谐波发射水平实施跟踪计算,以此就能对系统谐波阻抗及用户谐波发射水平进行准确的评估。另外,通过相应的仿真实验、实例分析,验证了这种评估方法的可行性。     

微电网HHT谐波检测与时频分析方法

为解决微电网谐波、突变等复杂非平稳信号的精确检测问题,提出一种基于Hilbert-Huang变换（HHT）的微电网谐波检测与时频分析方法。该方法采用保形分段三次埃尔米特插值法拟合极值点曲线,对谐波信号进行经验模态分解（EMD）,得到有限个固有模态分量（IMF）并进行Hilbert变换,最终计算各个IMF分量的瞬时频率和瞬时幅值,实现微电网谐波等非平稳电能信号的时频特性精确检测。仿真结果表明,该方法能够快速、准确地获取谐波信号频率成分、幅度及电压突变时刻。相对于FFT变换及传统HHT方法具有较高的精度和时域区分特性,可满足微电网谐波微机检测的工程应用需求。     

Adaptive harmonic control

This paper presents adaptive feedback control at individual harmonics for cancellation of periodic disturbances. It is shown that the original idea, that has been around for a long time, can be developed much further to produce robust and highly adaptable controllers. Frequency selective feedback harmonic cancellation (FHC) is presented. Simulations illustrate the effectiveness of the method.     

基于APF的谐波补偿中的几种谐波电流检测方法

采用有源电力滤波器（APF）已成为谐波补偿的一种重要趋势，而采用这种方式的关键是能够准确地检测出谐波电流，本文介绍了几种基于APF的谐波补偿中的谐波电流检测方法，并对它们进行了比较。     

Controllability of quantum harmonic oscillators

It is proven in a previous paper that any modal approximation of the one-dimensional quantum harmonic oscillator is controllable. We prove here that, contrary to such finite-dimensional approximations, the original infinite-dimensional system is not controllable: Its controllable part is of dimension 2 and corresponds to the dynamics of the average position. More generally, we prove that, for the quantum harmonic oscillator of any dimension, similar lacks of controllability occur whatever the number of control is: the controllable part still corresponds to the average position dynamics. We show, with the quantum particle in a moving quadratic potential, that some physically interesting motion planning questions can be however solved.     

Spherical harmonic molecular surfaces

Starlike surfaces can be defined in spherical coordinates by a function r(&thetas;, φ) on the unit sphere, which can be expanded in spherical harmonics to give a consequence of smooth approximations to the surface. This method has been used to approximate the solvent-accessible surface of a molecule. The coefficients in the expansion provide a small collection of numbers that characterize the molecular shape. The resulting smooth surfaces can be rendered with random dots or smooth shading. These spherical harmonic surfaces have advantages for modeling overall molecular shape, particularly time-averaged shapes relevant to electrostatic and other intermolecular interactions     

Fuzzy harmonic mean operators

Harmonic mean is a conservative average, which is widely used to aggregate central tendency data. In the existing literature, the harmonic mean is generally considered as a fusion technique of numerical data information. In this paper, we investigate the situations in which the input data are expressed in fuzzy values and develop some fuzzy harmonic mean operators, such as fuzzy weighted harmonic mean operator, fuzzy ordered weighted harmonic mean operator, fuzzy hybrid harmonic mean operator, and so on. Especially, all these operators can be reduced to aggregate interval or real numbers. Then based on the developed operators, we present an approach to multiple attribute group decision making and illustrate it with a practical example. © 2008 Wiley Periodicals, Inc.     

Kernel approximately harmonic projection

Dimensionality reduction is an important preprocessing procedure in computer vision, pattern recognition, information retrieval, and data mining. In this paper we present a kernel method based on approximately harmonic projection (AHP), a recently proposed linear manifold learning method that has an excellent performance in clustering. The kernel matrix implicitly maps the data into a reproducing kernel Hilbert space (RKHS) and makes the structure of data more distinct, which distributes on nonlinear manifold. It retains and extends the advantages of its linear version and keeps the sensitive to the connected components. This makes the method particularly suitable for unsupervised clustering. Besides, this method can cover various classes of nonlinearities with different kernels. We experiment the new method on several well-known data sets to demonstrate its effectiveness. The results show that the new algorithm performs a good job and outperforms other classic algorithms on those data sets.     

Linear dynamic harmonic regression

Among the alternative unobserved components formulations within the stochastic state space setting, the dynamic harmonic regression (DHR) model has proven to be particularly useful for adaptive seasonal adjustment, signal extraction, forecasting and back-casting of time series. First, it is shown how to obtain AutoRegressive moving average (ARMA) representations for the DHR components under a generalized random walk setting for the associated stochastic parameters; a setting that includes several well-known random walk models as special cases. Later, these theoretical results are used to derive an alternative algorithm, based on optimization in the frequency domain, for the identification and estimation of DHR models. The main advantages of this algorithm are linearity, fast computational speed, avoidance of some numerical issues, and automatic identification of the DHR model. The signal extraction performance of the algorithm is evaluated using empirical applications and comprehensive Monte Carlo simulation analysis.     

便携式谐波监测系统设计

为实现对外场设备中电源谐波的快速准确监测,提出了一种基于Labwindows/CVI的通用谐波监测系统设计方案。系统采用便携式工控机作为硬件平台,软件采用Labwindows/CVI软件作为开发平台,用来实现数据的采集、分析与处理等功能,并将小波补偿的加窗插值F F T算法用于进行谐波分析,提高了谐波分析精度。