Power system harmonic estimation using biogeography hybridized recursive least square algorithm

This paper presents a new hybrid method based on biogeography-based optimization (BBO) and recursive least square (RLS) algorithms, called BBO–RLS, to solve harmonic estimation problem in case of time varying power signal in presence of different noises. BBO algorithm searches for the global optimum mainly through two steps: migration and mutation. The basic BBO algorithm is combined with RLS in an adaptive way to sequentially update the unknown parameters (weights) of the harmonic signal. Practical validation is also made with the experimentation of the algorithm with real time data obtained from a solar connected inverter system panel with power quality analyzer and estimation is performed under simulation. Comparison of the results achieved with the proposed algorithm demonstrates its superiority over other recently reported five algorithms like GA, PSO, BFO, F-BFO with Least Square (LS), and BFO–RLS in terms of accuracy, convergence and computational time.     

Power system harmonic parameter estimation using Bilinear Recursive Least Square (BRLS) algorithm

The impact of nonlinear loads produces harmonic pollution in electrical power system. It is considered as a serious concern now a day. Whereas, many algorithms have been proposed for harmonic estimation to improve the power quality performance but till date the accurate estimation of power quality parameters remains a challenge. In this paper a non-linear adaptive algorithm, called Bilinear Recursive Least Square (BRLS), has been applied for the first time for estimating the amplitudes, phases and frequency in case of time varying power signals containing harmonics, sub harmonics, inter harmonics in presence of White Gaussian Noise. The technique is applied and tested for both stationary as well as dynamic signals containing harmonics. Practical validation of the proposed algorithm is also made along with the real time data obtained from a Variable Frequency Drive (VFD) panel used for controlling the speed and torque of the induction motor used at a large paper industry. Comparison of the results achieved with the proposed BRLS algorithm with two recently reported non-linear adaptive algorithms, Volterra Least Mean Square (VLMS), and Volterra Recursive Least Square (VRLS), reveals that the proposed BRLS algorithm is the best in terms of estimation accuracy and computational time.     

Variable Constraint based Least Mean Square algorithm for power system harmonic parameter estimation

This paper presents the maiden application of a novel signal processing algorithm called Variable Constraint based Least Mean Square (VCLMS) for power system harmonic parameter estimation. The amplitude, phase and frequency of a power signal containing harmonics, sub-harmonics, inter-harmonics are estimated using this algorithm in the presence of white Gaussian noise under simulating environment. Four Least Mean Square (LMS) based algorithms, reported in the literature are considered for judging the comparative performance with the proposed algorithm. These algorithms are applied and tested for both stationary as well as dynamic signals containing harmonics. Practical validation is made with the experimentation of the algorithms with real time data obtained from a solar connected inverter system used for supplying electrical energy during power cut at National Institute of Technology (NIT) Silchar through a power quality analyzer and estimation are performed in MATLAB simulation. Comparison of the results amongst LMS, Normalized LMS, Complex Normalized LMS, Variable Leaky LMS and VCLMS algorithms reveals that proposed VCLMS algorithm is the best in terms of accuracy and computational time.     

Experimental evaluation of envelope tracking techniques for voltage disturbances

In this paper a digital signal processor (DSP) based real time voltage envelope tracking system is developed and examined. The ADAptive LINEar neuron (ADALINE) and the Recursive Least Square (RLS) algorithms are adopted for envelope tracking. The proposed ADALINE and RLS algorithms give accurate results even under rapid dynamic changes. The paper investigates the effects of different parameters on the performance of the ADALINE algorithm and that of the RLS algorithm. The experimental system is cantered around a Texas Instrument 16 bit fixed-point arithmetic (TMS320LF2407A) evaluation board. Both the ADALINE and the RLS tracking algorithms are developed using the DSP-assembly language. A simple voltage flicker generator is implemented to produce various voltage disturbances. Extensive tests of the proposed envelope tracking algorithms are conducted to evaluate their dynamic performance.     

Improved Recursive Newton Type Algorithm based power system frequency estimation

This paper presents power system frequency estimation by using an Improved Recursive Newton Type (IRNTA) algorithm. The proposed approach uses Jacobian and covariance matrices for updating the unknown parameters. The recursive form of unknown parameters and covariance matrix are incorporated in the algorithm to have faster convergence. The performance of the proposed algorithm is studied through simulations and experiments for several critical cases that often arise in a power system. Efficacy of the proposed algorithm is also compared with other signal processing techniques such as Recursive Least Square (RLS) and Kalman Filter (KF). Studies made on industrial data also support for the superiority of the proposed algorithm.     

基于自感知执行器原理的调谐滤波器

根据自感知执行器的工作原理,利用一只变压器完成谐波检测和抑制两种功能,处于正常工作状态时可实现谐波抑制,处于非正常工作状态时不致放大谐波。首先对工频信号进行数字采样,再利用自相关函数法结合递推最小二乘估计工频信号的频率,再根据该频率产生反向抑制谐波,来抑制当前谐波。为实时调整各次反向抑制谐波的权重,根据当前时刻的谐波抑制的结果,采取最小均方自适应算法来更新权重。模拟试验表明,该调谐滤波器具有良好的控制特性。     

A new SPARLS algorithm for tuning power system stabilizer

Generators have to meet the change in real and reactive power demand of practical power system. The real power variations in the system are met out by the rescheduling process of the generators. But there is a huge trust to meet out the reactive power load demand. The excitation loop of the corresponding generator is adjusted with its electric limits to activate the reactive power of the network. To expedite the reactive power delivery, power system stabilizer (PSS) is connected in the exciter loop of the generator for various system conditions. In this paper, a new Sparse Recursive Least Square (SPARLS) algorithm is demonstrated to tune the power system stabilizer parameters to meet the vulnerable conditions. The proposed SPARLS algorithm makes use of expectation maximization (EM) updation to tune the PSS. A comparative study between the proposed SPARLS and RLS algorithm has been performed on single machine infinite bus system (SMIB). The simulation results obtained will validate the effectiveness of the proposed algorithm and the impact of stability studies of the power system operation under disturbances. The SPARLS algorithm is also used to tune the parameters of PSS to achieve quicker settling time for the system parameter such as load angle, field voltage and speed deviation. It is found that the SPARLS is a better algorithm for the determination of optimum stabilizer parameter.     

智能保护算法的研究

介绍了目前在电力系统智能保护算法中广泛研究的几种算法,包括傅氏算法及其改进算法;最小二乘法及其递推算法;小波分析算法。文中详细介绍了这几种智能保护算法尤其是改进的傅氏算法,最小二乘法递推算法,小波分析算法的内容、应用场合及优缺点,并展望小波分析和傅氏算法相结合的新方法。最后通过对这些算法分析、比较,在需要快速切断的场合下,得出更优智能保护算法是改进的傅氏算法,最小二乘法递推算法。     

Several variants of Kalman Filter algorithm for power system harmonic estimation

This paper presents the maiden application of a variant of Kalman Filter algorithm known as Local Ensemble Transform based Kalman Filter (LET-KF) for power system harmonic estimation. The proposed algorithm is applied for estimating the harmonic parameters of a power signal containing harmonics, sub-harmonics, inter-harmonics in presence of white Gaussian noise. These algorithms are applied and tested for both stationary as well as dynamic signals containing harmonics. The LET-KF algorithm reported in this paper is compared with the earlier reported Kalman Filter based algorithms like Kalman Filter (KF) and Ensemble Kalman Filter (EnKF) algorithms for harmonic estimation. The proposed algorithm is found superior than the reported algorithm for its improved efficiency and accuracy in terms of simplicity and computational features, since there are less multiplicative operations, which reduces the rounding errors. It is also less expensive as it reduces the requirement of storing large matrices, such as the Kalman gain matrix used in other KF based methods. Practical validation is carried out with experimentation of the algorithms with the real time data obtained from a large paper industry. Comparison of the results obtained with KF, EnKF and LET-KF algorithms reveals that the proposed LET-KF algorithm is the best in terms of accuracy and computational efficiency for harmonic estimation.     

基于RLS自适应算法的APF电流检测

有源电力滤波器(APF)电流检测算法使用低通滤波器(LPF)提取基波有功直流分量,直流分量的提取精度直接影响着指令电流信号的计算精度。提出一种应用数字递推最小二乘法(RLS)替代模拟LPF的电流检测新方法。RLS自适应滤波算法是在采样周期内对整体采样序列进行滤波器权系数最优化搜索,即对权系数迭代中的步长寻优,从而准确地跟踪输入信号的直流分量。新方法以瞬时无功功率理论为电流检测依据,利用坐标、三角变换矩阵根据电网三相瞬时电流计算出电流瞬时有功、无功交/直流分量。应用Matlab软件编写RLS自适应滤波算法程序进行仿真,结果表明APF电流检测中采用数字RLS自适应滤波提取直流分量的方法是可行、有效的。     

Harmonic estimation in a power system using a novel hybrid Least Squares-Adaline algorithm

Nowadays many algorithms have been proposed for harmonic estimation in a power system. Most of them deal with this estimation as a totally nonlinear problem. Consequently, these methods either converge slowly, like GA algorithm [U. Qidwai, M. Bettayeb, GA based nonlinear harmonic estimation, IEEE Trans. Power Delivery (December) 1998], or need accurate parameter adjustment to track dynamic and abrupt changes of harmonics amplitudes, like adaptive Kalman filter (KF) [Steven Liu, An adaptive Kalman filter for dynamic estimation of harmonic signals, in: 8th International Conference On Harmonics and Quality of Power, ICHQP’98, Athens, Greece, October 14–16, 1998]. In this paper a novel hybrid approach, based on the decomposition of the problem into a linear and a nonlinear problem, is proposed. A linear estimator, i.e., Least Squares (LS), which is simple, fast and does not need any parameter tuning to follow harmonics amplitude changes, is used for amplitude estimation and an adaptive linear combiner called ‘Adaline’, which is very fast and very simple is used to estimate phases of harmonics. An improvement in convergence and processing time is achieved using this algorithm. Moreover, better performance in online tracking of dynamic and abrupt changes of signals is the result of applying this method.     

A hybrid least squares-GA-based algorithm for harmonic estimation

Harmonic estimation in a distorted signal along with additive noise has been an area of interest for researchers in many disciplines of science and engineering. This paper presents a new algorithm to estimate the harmonics in power systems using genetic algorithms (GAs). The harmonic estimation problem is linear in amplitude and nonlinear in phase. The proposed hybrid algorithm takes advantage of this structure and iterates between linear least squares amplitude estimation and the nonlinear GA-based phase estimation. Improvement in both convergence for solution as well as processing time is demonstrated from this algorithm.     

Improved frequency dynamic in isolated hybrid power system using an intelligent method

The Isolated Hybrid Distributed Generation (IHDG) studied in this paper is consisted of a wind turbine generator and a diesel engine generator. The equivalent inertia of power grid reduces by increasing influence of variable speed wind turbines in power systems. Consequently, when a disturbance occurs in the power system the frequency fluctuations increases. To overcome this problem, a supplementary control loop is added to the converter of the variable speed wind turbine in order to share the inertia of the turbines in the power grid. But the appropriate rate of this contribution depends on the amount of load and must be suitably changed based on the load. In this paper, a Takagi–Sugeno (T–S) fuzzy system is designed to determine the contribution coefficient of variable speed wind turbine in such a way that variable wind turbine shares the maximum value of its inertia to compensate the reduced production in the power grid. However, the turbine does not pass its minimum speed limit while sharing the maximum value of inertia in the grid and prevents the cause of another disturbance in the power grid. In the proposed method, first, by using Particle Swarm Optimization (PSO) algorithm, the optimal values of contribution coefficient of wind turbines are attained proportional to the load in such a way that the minimum speed constraint is not violated. In the next stage, the initial T–S fuzzy system is extracted from the obtanied the optimal values of contribution by using subtractive clustering algorithm. In addition, Recursive Least Square (RLS) algorithm is used to adjust the consequent part of the T–S system. The efficiency of the proposed method is demonstrated through the simulation for different amount of load.     

Novel schemes used for estimation of power system harmonics and their elimination in a three-phase distribution system

Estimation of power system harmonics and their elimination is an interdisciplinary area of interest for many researchers. This paper presents Variable Step Size Least Mean Square (VSS-LMS) approach for harmonics estimation and Shunt Active Power Filter (SAPF) with two-level Hysteresis Current Control (HCC) technique for their elimination in a three-phase distribution system. In the estimation process, the weight is updated using VSS-LMS algorithm. Harmonics components are estimated from the updated weights. In order to mitigate harmonics produced by the nonlinear load connected in a three-phase distribution system, SAPF with two-level HCC is proposed. A three-phase insulated gate bipolar transistor (IGBT) based current controlled voltage source inverter (CC VSI) with a dc bus capacitor is used as an active power filter. The first step is to calculate SAPF reference currents from the sensed nonlinear load currents by applying the synchronous detection method and then the reference currents are fed to the proposed controller for generation of switching signals. The nonlinear load consists of one three-phase and one single-phase diode rectifier feeding R–L load, so that the effectiveness of the two-level HCC scheme to compensate for unbalanced nonlinear load can be tested. Various simulation results are presented to verify the good behavior of the SAPF with proposed two levels HCC.     

注入式混合型有源电力滤波器的电流控制新策略

该文首先分析注入式混合型有源滤波器(injection hybrid active power filter,IHAPF)的结构特点,进而建立起对其进行电网侧谐波电流零逼近控制的模型。文章把比例积分(proportional integral,PI)控制算法运用于这一控制当中,以使系统稳态无静差;为改善系统的动态性能,用模糊算法对PI控制的系数进行在线调整;为提高系统的控制精度和稳定性,用选择谐波分次预补偿相位的方法来进行谐波检测,实现对系统延时的分频率补偿,提高系统的控制精度和稳定性。仿真结果和工程实际应用均表明,文章提出的控制方法能满足IHAPF系统控制的要求。     

一种用于高压混合有源电力滤波器的复合控制方法

针对一种适用于高压交流系统的混合有源电力滤波器结构,提出了新的复合控制方法,较好地满足了谐波补偿控制系统稳定性和补偿精度的要求。该方法能精确补偿事先指定的若干次负载谐波电流,同时能削弱泄漏到系统中其余次数的谐波电流,并可以阻尼滤波器支路和系统阻抗间可能的谐振。该方法滤波效果好,实现简单,适用于高压交流系统的谐波补偿。仿真和实验结果证明了复合控制方法的有效性。     

基于CPSO-RLS的电力系统谐波估计融合算法

针对非线性动态负载引起的谐波检测难的问题,提出了一种新的估计电力系统谐波的算法。该算法首先利用混沌粒子群算法(CPSO)的全局搜索性,对未知参数进行优化估计,然后将CPSO算法优化的值作为RLS算法模型的初始权值;最后借助RLS算法进行谐波的有效提取。通过实验仿真,与CPSO算法相比,谐波振幅估计精度最大提高7%,相角估计精度最大提高1.24%。仿真结果表明,该算法在保证收敛速度的同时具有更高的估计精度。     

Harmonic estimation using RLS algorithm and elimination with improved current control technique based SAPF in a distribution network

This paper presents the application of well known recursive least square (RLS) harmonic estimation technique and its elimination with improved current control technique based shunt active power filter (SAPF) in a distorted power network. The estimation of amplitude and phase angle of fundamental and harmonics is performed using RLS algorithm, known for their simplicity of computation, accuracy and good convergence properties. The estimates are updated recursively as samples of the harmonic signals are received. In order to eliminate harmonics produced by the nonlinear load connected in the distribution network, a three-phase SAPF with modified current control technique is employed. In this paper, based on the analysis and modeling of SAPF with closed-loop control, a feed forward compensation path of load current and a new pulse width modulation (PWM) control scheme is proposed to improve the dynamic performance of the SAPF. In this case the amplitude and phase angle of the converter AC voltage should be adjusted using PWM, thus producing either leading or lagging reactive power. Harmonic contented in the signal is estimated at the point of common coupling (PCC) with and without SAPF. The comparative results of amplitude and phase angle of fundamental and selected harmonics are determined considering installation of SAPF in the distribution network. The system is studied using MATLAB environment to justify the effectiveness of proposed control technique in comparison to the other techniques discussed in the recent literature.     

Real‐valued MUSIC algorithm for power harmonics and interharmonics estimation

Recently, advanced spectrum estimation methods, including the MUSIC (Multiple Signal Classification) algorithms, are being gradually employed for high‐resolution power harmonics analysis. However, most of them are proposed to detect frequencies of complex‐valued signals, so that any real‐valued signal should be transformed into complex form. This data pre‐treatment may lead to additional computation burden. In addition, the picket‐fence effects also exist as in the FFT algorithm and cause poor frequency resolution. To overcome these drawbacks, a real‐valued MUSIC algorithm is proposed for power harmonics analysis in this paper. The algorithm is based on the subspace decomposition theory and the computation of pseudospectrum is also provided. Additionally, to improve the measuring precision, the Newton–Raphson algorithm is adopted to optimize the harmonic frequencies significantly. Simulation results show that, in the real‐valued MUSIC pseudospectrum, the spectral peaks of actual harmonic components can be more easily distinguished from the false peaks caused by noise, and the computational complexity is notably lower than that of the classic complex MUSIC, as well as the detecting accuracy is close to that of root‐MUSIC algorithm which is quite time consuming. Experimental results prove that the proposed strategy is more suitable for high‐resolution power harmonics estimation. Copyright © 2010 John Wiley & Sons, Ltd.     

空间双通道电机噪声有源控制系统研究

针对实验室一台直流电动机-同步发电机机组运行噪声的频谱特点,提出空间双通道有源噪声控制系统降低电机运行噪声。采用四种双通道控制算法(Ⅰ)FxLMS算法,(Ⅱ)FuRLMS算法,(Ⅲ)HFxLMS算法以及(Ⅳ)FBFxLMS算法进行电机运行噪声有源控制实验,对于电机运行转速分别为1300 r/min、1400 r/min和1500 r/min时,噪声控制区域内水平平面和垂直平面上平均声压级降低量均大于10 dB,水平平面上最大声压级降低量分别为17.92 dB、13.28 dB和17.88 dB,垂直平面上最大声压级降低量分别为16.73 dB、16.36 dB和16.99 dB,降噪效果表明本文提出的空间双通道有源控制系统能有效地降低电机运行噪声。