Detection and tracking of short duration variations of power system disturbances using modified potential function

This study introduces a modified potential function based modeling approach for real-time disturbance tracking. Real-time tracking requires the least complex techniques for processing and classification and still provide accurate results. Time required to detection of the power quality disturbance should be small enough so that the further mitigation action may be taken. The proposed FRTD algorithm is able to detect the disturbances in 3–5 samples. The proposed FRTD algorithm is principally based upon potential function, which has been modified so as to give the one-dimensional position vector corresponding to the voltage sag and swell, with complexity O(1) with no pre-process complexity. The method detects the transient in 3–5 samples at sampling frequency of 12.8 kHz. Potential function uses the current nonlinear drift velocity vector along with a prior knowledge of the power system disturbance to compute the unknown parameter in the form of diffusion matrix, D_t. The parameter D_t has been used to detect the events in the signal. Magnitude of D_t play vital role to detect the events. FRTD algorithm has been tested to track and detect the power system disturbances such as voltage sag, swell, and transient. The algorithm has been tested on hardware interfaced with MATLAB. 1000 samples of different types of power system disturbances such as voltage swell, voltage sag, oscillatory-transient and impulsive-transient have been tested. FRTD algorithm is having the efficiency of 99.83%.     

基于复小波变换和Teager能量算子的电压跌落检测方法研究

针对电压跌落的跳变相位、起止时刻和跌落幅值这三个特征量有效检测问题,提出了基于复小波变换和Teager能量算子的电压跌落检测方法。详细研究了复小波的构造原理以及它和Teager能量算子在检测电压跌落上的应用。对于含噪的电压跌落信号,利用Teager能量算子对db4复小波变换后得到的近似信号进行跌落幅值的检测,利用db4复小波变换检测发生跌落前后的两个近似信号的相位,以相位差的形式得出电压跌落发生的起止时刻与跳变相位。Matlab仿真结果验证了算法的抗干扰性与实时性。     

基于复小波变换和有效值算法的电压暂降检测方法

对电压暂降三大特征量即持续时间、相位跳变和幅值的准确检测是实现电压暂降有效补偿的前提。文中提出复小波变换和有效值算法相结合的电压暂降检测方法。详细研究了复小波变换奇异性检测原理及其在电压暂降起止时间检测中的应用,采用具有四阶消失距的复Gaussian小波(Cgau4)能准确检测电压暂降发生、恢复时刻和相位跳变,利用有效值算法实现电压暂降幅值的检测。通过在Matlab中对有无畸变情况下的的电压暂降问题建模仿真,验证了该算法的有效性,实验结果表明该方法能精确检测电压暂降三大特征量。     

小波包变换在电能质量扰动检测中的应用

鉴于小波包变换能够均匀划分信号频带,聚焦任意频率,是暂态电能质量扰动分析的良好工具,提出了在噪声环境中电能质量扰动检测和定位的有效方法,即利用小波包变化模极大值原理定位电力系统短时扰动并确定扰动持续时间。仿真表明,通过小波包一、二次分解和重构能更好地提取扰动特征信息,从而为电能质量的检测、评估及治理提供依据,且该算法计算简单、快速、有效。     

采用小波变换和同相位补偿的不间断动态电压恢复器

为消除瞬时电压扰动,提高电压质量,在介绍了不间断运行动态电压恢复器(UDVR)的工作原理、拓扑结构、工作模式及电压补偿策略后,提出了应用小波变换来检测动态电压恢复器中电压畸变特征量的方法,该算法对电源电压发生跌落、骤升、三相不平衡、伴随谐波等运行工况实现了畸变分量幅值和相位的无延时检测。以最新的三单相电压源型逆变电路独立补偿主电路取代传统的三相同时补偿,对UDVR在不同工况下的动态电压补偿特性进行了仿真实验研究。结果表明采用小波变换的UDVR具有较好的实时性和补偿灵活度,可以有效地抑制电网中各种电压暂态扰动,是解决电压型电能质量问题的有效手段,能满足敏感电力负荷在复杂电压暂态环境下的不间断运行。     

基于小波变换模极大值的电能质量扰动检测与定位

随着各种敏感电力电子设备在工业中的广泛应用,诸如短时低电压、短时过电压等电能质量扰动问题已成为近年来各方面的关注的焦点。对于短时低电压扰动发生、恢复时刻的检测与定位则电能质量监测和统计中获取相关指标首先要解决的问题。该文对小波变换模极大值检测原理及其在和短时低电压、短时过电压扰动信号检测中的应用进行了详细的研究,通过检测小波变换模极大值,实现了对短时低、短时过电压扰动发生、恢复时间的精确定位。仿真计算结果表明上述检测方法是有效的。     

An active islanding detection scheme for inverter-based DG with frequency dependent ZIP–Exponential static load model

In this paper an analytical design method is proposed for constant voltage controlled inverter based DG with frequency dependent ZIP–Exponential static load model to obtain proper inverter output control and successful islanding detection. The proposed technique is aimed to eliminate the dependency of DG operation point on anti-islanding performance which is unavoidable in case of traditional control strategy. The generalized formulae are derived for calculating the upper and lower limits of the voltage gain, and it is recommended to select the voltage gain within the designed range for effective islanding detection. The proposed approach is tested in MATLAB/Simulink environment and result shows that the proposed scheme is found to be highly effective in islanding detection considering complex network configurations with single and multiple DG systems. The proposed control scheme is able to detect islanding within 10 ms (half cycle) from the event inception, showing the fastness of the developed technique. It is also observed that the percentage of voltage and current THD of the proposed scheme is within permissible limits, indicate that the power quality of the inverter is not degraded by the proposed control strategy, and thus overcomes the drawback of existing active anti-islanding techniques.     

基于概率神经网络和双小波的电能质量扰动自动识别

对电能质量(PQ)扰动的自动识别是找出引起PQ问题根本原因的前提。提出了一种基于概率神经网络PNN(Probabilistic Neural Networks)和db10,db1双小波的PQ扰动自动识别方法。首先,利用db10小波对信号进行分解,将各层小波变换系数的能量和第1高频层模极大值情况作为PNN的输入矢量,判断扰动类型;然后,对信号进行傅里叶变换以检测信号中是否含有谐波;最后,对判断存在电压下降的信号进行db1小波分解,根据其低频层的模值区分电压下陷和电压中断信号。测试结果表明,该方法提高了识别正确率,且实现简单,能有效检测幅值较小的谐波。     

一种简单的电能质量扰动信号检测方法

提出了一种简单的电能质量扰动检测方法,用于判断采集信号中是否存在电能质量扰动,作为扰动分类的前提。该方法利用当前周期的电压信号与前一个周期信号之间的差值信号来进行电压凹陷、电压凸起及暂态振荡、暂态脉冲等暂态电能质量问题检测,利用差分信号和滤波后低频和高频信号的能量比来检测稳态电能质量问题。该方法实现简单,计算量小,检测全面,可以实时、在线完成,弥补了以往采用小波或小波包变换方法复杂费时以及准测不全面的不足,也弥补了单独采用差值信号方法无法检测稳态电能质量问题的缺陷。仿真和试验结果表明了本文提出方法的可行性和有效性。     

采用小波多分辨率信号分解的电能质量检测

针对典型的电能质量扰动信号 ,提出了采用小波多分辨率信号分解的电能质量检测与时频分析方法 ,并提出一种新型的同步检波器。该方法将电能质量扰动信号分解到子频带中 ,在小波域上检测信号的时间、频率和幅度 ,具有突出信号时域、频域局部特征的能力 ,因此特别适用于短暂瞬时信号的检测与分析。仿真结果表明 ,该方法具有优异的检测性能 ,适用于电压凹陷、电压凸起、电压间断、短时间谐波失真、暂态谐波失真、电压闪变与波动等电能质量扰动信号的检测与时频分析。     

Direct power control of a multilevel inverter based active power filter

A cascaded H-bridge multilevel inverter based active power filter with a novel direct power control is proposed in this paper. It can be directly connected to medium/high voltage power line without using the bulky transformer or passive filter. Due to the limited switching frequency (typically below 1 kHz) of high-power solid-state devices (GTO/IGCT), multiple synchronous/stationary reference frame current controllers are reviewed and derived. Based on this, a novel current controller is proposed for harmonic current elimination and system power factor compensation. Furthermore, a synchronous/stationary hybrid structure can be derived with fundamental de-coupling control. The instantaneous reactive power theory and synchronous reference frame based control are compared based on mathematical models. A direct power control concept is then derived and proposed. It is equivalent as the hybrid synchronous/stationary frame current controller, but has a simpler implementation. It has clear physical meaning and can be considered as a simplified version of the hybrid frame current controller. Simulations on a 4160 V/1.2 MVA system and experimental results on a 208 V/6 kVA laboratory prototype are presented to validate the proposed active power filter design.     

Energy management strategy for fuel cell/battery/ultracapacitor hybrid vehicle based on fuzzy logic

In order to enhance the fuel economy of hybrid vehicle and increase the mileage of continuation of journey, a fuzzy logic control is utilized to design energy management strategies for fuel cell/battery (FC + B) hybrid vehicle and fuel cell/battery/ultra-capacitor (FC + B + UC) hybrid vehicle. The models of hybrid vehicle for FC + B and FC + B + UC structure are developed by electric vehicle simulation software ADVISOR which uses a hybrid backward/forward approach. The results demonstrate that the proposed control strategy can satisfy the power requirement for four standard driving cycles and achieve the power distribution among various power sources. The comprehensive comparisons with the power tracking control strategy which is wide adopted in ADVISOR verify that the proposed control strategy has better rationality and validity in terms of fuel economy and dynamic property in four standard driving cycles. Therefore, the proposed strategy will provide a novel approach for the advanced energy management system of hybrid vehicle.     

Low cost microcontroller based fault detector,classifier, zone identifier and locator for transmission lines using wavelet transform and artificial neural network: A hardware co-simulation approach

A low cost, fast and reliable microcontroller based protection scheme using wavelet transform and artificial neural network has been proposed and its effectiveness evaluated in real time. The proposed scheme, based on the hardware co-simulation approach performs all the functions of transmission line protection i.e. fault detection/classification, fault zone/section identification and location estimation. The fault detection/classification and zone identification algorithms use fundamental frequency current component to estimate a fault index. The fault location estimation module uses wavelet transform coefficients in hybridization with a parallel artificial neural network structure. For hardware implementation, a 8-bit ATmega microcontroller is used and interfaced with the simulated power system model using Integrated Development Environment (IDE). The scheme is tested on a power system model of 400 kV, 50 Hz three phase double circuit line with source at both the ends. Laboratory tests have been performed in real time for 20,000 fault cases including evolving faults with varying fault resistance, fault inception angle, fault distance, direction of power flow angle and its magnitude. The tests confirm the suitability and reliability of proposed scheme even with Current Transformer (CT) saturation. The implementation of the proposed approach on a low cost microcontroller with the lesser execution time, makes the prototype ideal for implementation on a digital platform (digital relay), thus leading to financial viability and sustainability of the protection scheme.     

基于数学形态学和短窗功率算法的电能质量扰动检测方法

提出了一种基于数学形态学和短窗功率算法的电能质量扰动检测及定位方法.根据数学形态学基本原理及其形态变换构造了一种简单实用的形态滤波器并将其运用于扰动信号预处理中,以同时滤除随机和脉冲噪声.该滤波方法能在滤除多种噪声的同时,较好地保留了扰动信号的基本形态特征,较之小波方法和传统形态滤波方法更为有效.根据扰动位置能量的变化,对滤波后的信号利用短窗功率算法以准确地检测出扰动并进行时间定位.分别用电压暂升、暂降、中断和短时电压波动对该方法进行验证,Matlab仿真结果表明了该方法的有效性.     

用小波变换和有效值算法实现电压凹陷的准确测量

随着各种敏感用电设备的广泛应用，电压凹陷问题已成为近年来各方面关注的焦点。电压凹陷的衡量指标包括幅值、持续时间、频次和畸变度等，其中幅值和持续时间的精确测量是电压凹陷实时监测中首先要解决的问题。文中详细研究了小波变换模极大值原理在电压凹陷检测中的应用，提出了小波变换与有效值算法相结合的电压凹陷测量方法，克服了有效值算法不能精确测量持续时间的不足，仿真计算结果表明该方法是有效的。     

3-Phase 4-leg unified series–parallel active filter system with ultracapacitor energy storage for unbalanced voltage sag mitigation

This paper presents the analysis and design of a 3-phase 4-leg (3P4L) unified series–parallel active filter (USPAF) with ultracapacitor energy storage (UCES) for improving the power quality in three-phase four-wire (3P4W) distribution system. The series and parallel active filter (AF) of 3P4L USPAF system are realized by four-leg voltage source inverters (VSIs) to a common dc-link capacitor. Due to its high power density, the UCES is well-suited to supply high power for short period of time. The objective of this paper is to enhance the unbalanced voltage sag mitigating capability of the 3P4L USPAF system by adding UCES, directly connected in the dc-link. This is achieved by injecting energy from the UCES to maintain the dc-link voltage constant. Thus, the proposed system is capable of mitigating unbalanced voltage sag with zero-sequence component in the source voltage and compensating harmonic, reactive power and unbalanced current of the load in 3P4W distribution systems. The proposed scheme is validated by an experimental prototype with a 1.93 F UCES bank and using dSPACE DS1103 real-time control platform in the laboratory. The experimental results show that the combined system offer improved performance to maintain the load voltage constant at its rated value during unbalanced voltage sag in the supply voltage.     

基于小波和BP神经网络的电能扰动分类新方法

电能质量扰动的分类包括特征向量提取和分类器构建2部分。基于小波和神经网络的分类方法大部分采用小波分解各层的能量分布作为特征向量,用单个神经网络给出分类结果,此类方法构建的分类器性能有待进一步提高。文章构建了一组基于小波变换的特征向量作为分类器的输入。通过基于最小二乘法的策略综合3个相互独立神经网络的输出以得到最后的判别结果。算例表明提出的分类器准确率高,在信噪比20 dB的情况下还可以达到93.18%的准确率。分类器能有效识别电压中断、电压暂降、电压暂升、谐波、振荡暂态和闪变6种常见电能质量扰动。     

基于两个实值小波变换定量检测电能质量扰动的新方法

文章针对电压中断、电压下跌和电压上升这三种电压波形畸变进行了定量检测研究。提出了基于两个实值小波变换的修正幅值的新概念，并从理论上说明了该修正幅值具有如下的特性：(1)在非故障区间内取值均相等，且恰好等于额定电压的幅值；(2)在故障区间内(端点除外)取值也相同，且恰好等于故障区间内的电压的幅值；(3)与电压波形畸变所在相位、长度及电压的工频频率无关。文章还应用该修正幅值对这三种电压波形畸变进行了检测，检测图能定位故障发生、终止时刻和区分电能质量扰动的类型，并可定量测定出电压幅值上升或下降的幅度。     

Fast fault detection and classification based on a combination of wavelet singular entropy theory and fuzzy logic in distribution lines in the presence of distributed generations

This paper proposes a new method of fault detection and classification in asymmetrical distribution systems with dispersed generation to detect islanding and perform protective action based on applying a combination of wavelet singular entropy and fuzzy logic. In this method, positive components of currents at common coupling points are decomposed to adjust detailed coefficients of wavelet transforms and singular value matrices, and expected entropy values are calculated via stochastic process. Indexes are defined based on the wavelet singular entropy in positive components and three phase currents to detect and classify the fault. This protection scheme is put forward for fault detection and is investigated in different types of faults such as single-phase to ground, double-phase to ground, three-phase to ground and line to line in distribution lines in the presence of distributed generations, and different locations of faults are verified when the distributed generation is connected to the utility. The major priority of the proposed protection scheme is its reduction in time (10 ms from the event inception) in distinguishing islanding and protection transmission lines in the presence of distributed generations.     

A new wavelet network based method to estimate the lightning-related risk of failure of power system apparatus

This paper proposes a new and fast wavelet network based method for estimating the risk of failure caused by lightning overvoltages in arrester protected networks. First, failure risks obtained by simulations are used as the training data for training the wavelet network. The trained wavelet network is then used for accurate and fast estimating of the lightning-related risk of failure of power system apparatus for all possible conditions. The accuracy of the proposed method has been tested and verified under various conditions in the 230 kV network of Sistan–Baluchestan. Performance of the new method has also been compared with several existing methods under same conditions, and the test results show better accuracy of the proposed method. The proposed method not only does not have the restriction of conventional methods, but also it does not have the limitations associated with traditional neural networks based algorithms such as convergence to local optimum points, over-fit and/or under-fit problems. The main contribution of the paper is an accurate (due to proper selection of the training data set based on the k-fold cross validation technique and using wavelet network for estimation), fast (mean calculation time for the network risk of failure computation is 54 s) and simple wavelet network-based algorithm (as compared to the conventional algorithms) for estimating the lightning-related risk of failure of power system apparatus.