一种风电场用新型110 kV感应滤波变压器设计

该文首先介绍了我国目前风电场风力发电的谐波问题,分析感应滤波技术与传统抑制谐波的方法比较优势所在,介绍了感应滤波的原理和感应滤波变压器产生背景。从总体思路和技术方案两方面介绍了一种新型110 kV级风电场用感应滤波变压器的设计方案。根据试验结果,对关键参数进行分析,与同类风电场用变压器比较,优点突出,前景广阔。     

LF炉滤波器滤波效果计算方法浅析

阐述LF炉谐波产生原因及其特点,对采用二阶型滤波器来抑制LF炉产生谐波的滤波效果计算方法进行探讨。     

有源滤波器在烟草行业低压配电系统中的应用

本文介绍了有源滤波器在低压配电网络中的应用,通过实时监测供电线路中变频器、变速传动装置、各种直流电源等设备产生的高次谐波,动态抑制高次谐波,消除谐波电流对供电网络中设备的危害,降低能源的浪费,提高供电质量,保证供电设备及用电设备的安全运行。     

有源滤波装置节电性能分析

随着现代科学技术的发展，特别是大量新型、高效、多功能的非线性负荷增加，使得电网中的谐波污染越来越严重。为了保证电网的电能质量，大量用户开始采用有源滤波等技术进行谐波治理。本文主要就有源滤波装置的节电性能进行了探讨性的分析。     

论有源滤波技术在电力系统中的应用

随着科技的发展,生产过程中采用的大型设备的种类和数量越来越多,对电能质量的要求也越来越高。但是受多种因素的影响,电网中的电流波形严重偏离了正弦波,产生了谐波分量,影响了电能质量水平。有源滤波和无源滤波是目前常用的两种滤波方法,本文简要介绍了电网中谐波的危害,并且就有源滤波的特点和优势进行了介绍,给出了其未来发展前景。     

自适应控制算法在振动主动控制中的应用

通过试验研究主动控制振动传递的效果。采用频率在线估计和跟踪滤波的自适应控制方法,将以分量型式抑制谐波干扰引起的振动。在控制过程中,通过递推计算进行频率估计,用中心频率随动的带通滤波器进行信号跟踪,并在基本LMS方法的基础上形成自适应控制器。建立了多点控制试验台,实施跟踪滤波的自适应对消。结果表明：自适应方法能够很好地抑制谐波干扰的影响;对于多点隔振,控制通道之间存在强烈耦合作用,整体隔振效果与被控结构的振动模态相关。     

有源电力滤波器中的谐波检测研究

文章对现有的有源电力滤波器中的谐波检测方法进行了详细的分析,因而选择从自适应滤波的理论入手,分析了权值与瞬态响应速度的关系,推导出了一种改进的谐波检测方法,这种方法能够在半个基波周期内完成对谐波的检测,并且检测精度不受影响,最后用Matlab验证了其有效性。     

浅析电网谐波的产生、危害及消除

当今,谐波是损害电能质量的重要因素之一,对大部分设备的正常工作影响甚大,所以,谐波治理工作越来越受到关注。本文首先对电网谐波的产生及危害情况进行阐述,文章主要分析了电网谐波消除措施及优缺点,重点结合实例阐明磁通补偿型零序滤波装置的优良效果。     

柴油机排气噪声有源控制仿真研究

针对柴油机排气噪声设计了一套有源消声系统，并对高速数字信号处理芯片为基础的控制单元进行了仿真试验，该系统采用了转速信号作为次级声源输入，并以自适应同源谐波滤波为控制模型，保证了系统的有效性和稳定性，仿真结果表明，本系统有很好的消声效果。     

自适应滤波与相关滤波在冲击响应信号特征提取中的应用

识别冲击响应信号在模态分析和机械监测诊断研究中具有重要意义。由于噪声成分、工频及其谐波的干扰，机组运行或其他实际信号中的冲击响应信号很弱。这些冲击响应信号的特征也较难提取。选择适当的自适应滤波器参数，应用自适应滤波首先对信号进行预处理，去掉强大的工频及其谐波成分，使信号的信噪比得到很大的提高；然后利用Laplace小波相关滤波法对自适应滤波预处理后的信号进行进一步的处理，提取其模态信息。结果证明，将这两种方法结合后的信号特征提取效果是比较理想的。     

并网变流器三相谐波检测方法的研究

针对在电力系统中广泛应用的各种变频器、变流器、开关电源和电抗器会使电网中的谐波含量增加带来的诸多影响,该文介绍了并网发电系统中变流器谐波检测的重要性,分析了不同的三相谐波检测技术,并通过谐波检测技术提取并网变流器中电压/电压谐波,从跟踪和提取时变谐波上比较了三相谐波检测技术。     

交-直-交型电力机车网侧谐波对牵引变电所的影响及改进

本文分别对比介绍了新型交-直-交型大功率电力机车和以SS4为代表的传统型交-直型电力机车的主电路拓扑结构及其网侧电流谐波特性。由测试结果表明大功率电力机车与传统电力机车相比最显著的特征是其谐波特性不同,并分析了网侧谐波对牵引变电所电气设备造成的影响和采取的相应的技术改进措施,确保牵引供电系统的正常运行。     

Adaptive Fuzzy Logic Controller for Harmonics Mitigation Using Particle Swarm Optimization

An excessive use of non-linear devices in industry results in current harmonics that degrades the power quality with an unfavorable effect on power system performance. In this research, a novel control technique-based Hybrid-Active Power-Filter (HAPF) is implemented for reactive power compensation and harmonic current component for balanced load by improving the Power-Factor (PF) and Total–Hormonic Distortion (THD) and the performance of a system. This work proposed a soft-computing technique based on Particle Swarm-Optimization (PSO) and Adaptive Fuzzy technique to avoid the phase delays caused by conventional control methods. Moreover, the control algorithms are implemented for an instantaneous reactive and active current (I_d-I_q) and power theory (Pq0) in SIMULINK. To prevent the degradation effect of disturbances on the system's performance, PS0-PI is applied in the inner loop which generate a required dc link-voltage. Additionally, a comparative analysis of both techniques has been presented to evaluate and validate the performance under balanced load conditions. The presented result concludes that the Adaptive Fuzzy PI controller performs better due to the non-linearity and robustness of the system. Therefore, the gains taken from a tuning of the PSO based PI controller optimized with Fuzzy Logic Controller (FLC) are optimal that will detect reactive power and harmonics much faster and accurately. The proposed hybrid technique minimizes distortion by selecting appropriate switching pulses for VSI (Voltage Source Inverter), and thus the simulation has been taken in SIMULINK/MATLAB. The proposed technique gives better tracking performance and robustness for reactive power compensation and harmonics mitigation. As a result of the comparison, it can be concluded that the PSO-based Adaptive Fuzzy PI system produces accurate results with the lower THD and a power factor closer to unity than other techniques.     

Mathematical Morphology-Based Artificial Technique for Renewable Power Application

This paper suggests a combined novel control strategy for DFIG based wind power systems (WPS) under both nonlinear and unbalanced load conditions. The combined control approach is designed by coordinating the machine side converter (MSC) and the load side converter (LSC) control approaches. The proposed MSC control approach is designed by using a model predictive control (MPC) approach to generate appropriate real and reactive power. The MSC controller selects an appropriate rotor voltage vector by using a minimized optimization cost function for the converter operation. It shows its superiority by eliminating the requirement of transformation, switching table, and the PWM techniques. The proposed MSC reduces the cost, complexity, and computational burden of the WPS. On the other hand, the LSC control approach is designed by using a mathematical morphological technique (MMT) for appropriate DC component extraction. Due to the appropriate DC-component extraction, the WPS can compensate the harmonics during both steady and dynamic states. Further, the LSC controller also provides active power filter operation even under the shutdown of WPS condition. To verify the applicability of coordinated control operation, the WPS-based microgrid system is tested under various test conditions. The proposed WPS is designed by using a MATLAB/Simulink software.     

基于小波变换的电力系统谐波测量方法

小波变换具有时-频局部化特性,在电力系统的分析中具有无比广阔的应用前景.本文将小波变换方法应用于电力系统谐波检测中,并提出了同步检测与小波变换相结合的电压闪变测量方法,仿真结果表明此方法适用于电压闪变信号的检测和分析.     

Machine Learning and Data-Driven Techniques for the Control of Smart Power Generation Systems: An Uncertainty Handling Perspective

Due to growing concerns regarding climate change and environmental protection, smart power generation has become essential for the economical and safe operation of both conventional thermal power plants and sustainable energy. Traditional first-principle model-based methods are becoming insufficient when faced with the ever-growing system scale and its various uncertainties. The burgeoning era of machine learning (ML) and data-driven control (DDC) techniques promises an improved alternative to these outdated methods. This paper reviews typical applications of ML and DDC at the level of monitoring, control, optimization, and fault detection of power generation systems, with a particular focus on uncovering how these methods can function in evaluating, counteracting, or withstanding the effects of the associated uncertainties. A holistic view is provided on the control techniques of smart power generation, from the regulation level to the planning level. The benefits of ML and DDC techniques are accordingly interpreted in terms of visibility, maneuverability, flexibility, profitability, and safety (abbreviated as the “5-TYs”), respectively. Finally, an outlook on future research and applications is presented.     

On-Line Phase Measurement of Power System Harmonics

A new instrument which allows on-line measurements of the phase angle of harmonics is presented. It is used in conjunction with a wave analyzer and provides amplitude and phase angle of harmonics. The principle of the measurement is an analogue null detection, hence the accuracy depends practically only on the quality of the tuned voltmeter used. Direct digital read out is provided for the angle. Design criteria, practical implementation and actual performance are presented. The instrument has demonstrated great potential in the study of ferromagnetic devices, core-loss curves, and power system harmonics.     

超导电力装置失超检测的基础研究

超导电力装置的失超会影响超导电力设备的运行和安全，是超导电力设备技术实用化有待深入研究的一个重要问题。对国内外通用的超导装置失超检测方法进行了分析，并根据电力系统中超导装置失超检测的特点，对高温超导线材在不同幅值的动态电流作用下的失超特性进行了试验研究，通过对试验数据的分析，对高温超导线材的失超特性有了较精细的理解，并在此基础上提出了超导电力装置失超先兆检测及其失超保护设计的新概念。     

A Time-Domain Approach for the Analysis of Nonstationary Signals in Power Systems

Voltage and current waveforms produced by several power systems are often characterized by a wide spectrum that contains numerous components, namely the fundamental, harmonics, and interharmonics. They can be properly analyzed through discrete Fourier transform (DFT)-based methods only if they remain stationary in time; in fact, in the presence of nonstationary components, DFT-based approaches do not grant reliable results because of the absence of a well-defined periodicity interval. The digital signal processing method proposed in this paper aims at analyzing a large category of nonstationary signals observed in power systems. It is capable of analyzing waveforms produced by power systems that seemingly operate in steady-state conditions, in which time-varying components represent anomalies, as well as waveforms generated by some power apparatuses, which supply nonstationary waveforms by design. The wide range of applicability of the proposed method is granted by a suitable processing scheme, including distributed filtering and phase unwrapping operations. Distributed filtering operations are performed to distinguish and separately analyze the major components contained in complex waveforms. Phase unwrapping operations are needed in the presence of nonstationary components characterized by heavy drifts and/or large swings in frequency.      

电气化铁道对无功电能计量影响的研究

电气化铁道为电网注入了大量谐波电流,降低了电网电能质量.而目前谐波对无功电能表计量特性影响的研究还不完善.文章在传统无功功率定义的基础上,按照C.Budeanu频域法,给出谐波下非正弦无功功率的定义,并且比较了电气化铁道中谐波对目前无功计量两种电能表的准确度影响,给出了电气化铁道中无功电能表的选择原则.