Hardware and software architecture for power quality analysis

This paper presents a novel concept for power quality hardware and software architecture. Software tools related to detection, classification and characterization of power quality events can be integrated into a Distribution Control Center in which the interconnection between different subsystems is being carried out through the Internet allowing flexibility to the system. This system is implemented using wavelet analysis applied in all proposed algorithms. Different power quality events are taken as examples to illustrate the capabilities of the proposed method. The obtained results reveal that the proposed architecture is feasible to be implemented as an integral part of a control center system.The proposed system has the property of fast and accurate detection and classification of any power quality disturbance event and introduces a new PQ index determination that allows characterizing any type of disturbance including the non-periodic signals.     

Adaptive fuzzy backstepping control of three-phase active power filter

A backstepping controller (BC) and an adaptive fuzzy backstepping controller (AFBC) are proposed for three-phase active power filter (APF) in this paper. Firstly, the dynamic model for APF is build in which both the system parameter variations and external disturbance are considered. Then, the backstepping method is applied in the design of current control system to deal with the nonlinearity of APF. Moreover, the AFBC is developed by combining the backstepping approach with adaptive fuzzy strategy to attenuate the effect of parameter uncertainties and external disturbances. Fuzzy logic system is designed to estimate the unknown nonlinear function in the AFBC where the parameters are adjusted online by the adaptive law derived from the Lyapunov stability analysis to guarantee the tracking performance and stability of the closed-loop system. Simulation studies using the MATLAB/SimPower Systems Toolbox demonstrate that the proposed control strategies exhibit excellent performance in both steady state and transient operation.     

Hybrid Renewable Energy Source Combined Dynamic Voltage Restorer for Power Quality Improvement

In this paper, the hybrid photovoltaic-thermoelectric generator (PV-TEG) combined dynamic voltage restorer (DVR) system is proposed for the power quality disturbances compensation in a single-phase distribution system. The stable and precise level of input voltage is essential for the smooth and trouble-free operation of the electrically sensitive loads which are connected at the utility side to avoid system malfunctions. In this context, the hybrid PV-TEG energy module combined DVR system is proposed in this paper. With the support of the hybrid energy module, the DVR will perform the power quality disturbances compensation effectively with needed voltage and /or power. In the proposed system, the PV and TEG energy sources are connected electrically in series to produce adequate voltage for the DVR operation and the fractional factor-based variable incremental conduction (FFVINC) maximum power point tracking (MPPT) control algorithm is employed to extract the possible maximum power from the PV array. The intelligent fuzzy logic controller (FLC) is chosen for implementing the MPPT control algorithm. The half-bridge voltage source inverter (VSI) circuit and in-phase voltage compensation technique are used in the DVR for better power quality disturbances compensation. The performance and usefulness of the proposed DVR system are investigated by an extensive simulation study with four different modes of operation, the study results are confirmed that the proposed system promptly identifies the power quality disturbances for compensation. Moreover, the investigation proved that the combined PV and TEG energy module can provide better energy efficiency in converting solar irradiation into electricity.     

Smart control techniques for design of TCSC and PSS for stability enhancement of dynamical power system

This paper deals with the simultaneous application of thyristor controlled series capacitor based damping controller and power system stabilizer for stability improvement of dynamic power system. The adaptive neuro-fuzzy inference system and Levenberg–Marquardt artificial neural network algorithm are used to develop the control strategy for thyristor controlled series capacitor based damping controller and power system stabilizer. The power system stabilizer generates appropriate supplementary control signal to an excitation system of synchronous generator to damp the frequency oscillations and improves the performance of the power system dynamic. The performance of power system affected due to the system configuration and load variation. In order to achieve the appreciable damping, the series capacitor is suggested in addition to the power system stabilizer. Nonlinear simulations of single machine infinite bus system are carried out using the individual application of power system stabilizer and simultaneous application of power system stabilizer and thyristor controlled series capacitor. The comparison analysis between conventional and smart control strategies based controllers is demonstrated. Single machine infinite bus system is tested under various operating conditions and disturbances to show the effectiveness of proposed control schemes.     

基于自适应提升小波变换的电能质量检测节点

利用自适应提升小波变换和支持向量机进行电能质量扰动识别,将无线传感网络技术应用于电能质量无线检测系统。介绍了自适应提升小波变换算法和系统的软硬件架构,设计了以DSP和ARM为核心的电能质量检测节点,说明了TinyOS的移植和系统任务的设计过程。     

Optimum placement of active power conditioner in distribution systems using improved discrete firefly algorithm for power quality enhancement

This paper presents an improved solution for optimal placement and sizing of active power conditioner (APC) to enhance power quality in distribution systems using the improved discrete firefly algorithm (IDFA). A multi-objective optimization problem is formulated to improve voltage profile, minimize voltage total harmonic distortion and minimize total investment cost. The performance of the proposed algorithm is validated on the IEEE 16- and 69-bus test systems using the Matlab software. The obtained results are compared with the conventional discrete firefly algorithm, genetic algorithm and discrete particle swarm optimization. The comparison of results showed that the proposed IDFA is the most effective method among others in determining optimum location and size of APC in distribution systems.     

基于小波变换和FRVM的电能质量扰动分类

针对相关向量机(RVM)计算复杂度大、训练时间长的问题,提出一种基于快速相关向量机(FRVM)的优化算法,其大大减少了相关向量机的训练时间,提高了分类的精度.将它应用于电能质量扰动分类中,首先对电能质量扰动信号进行基于小波变换的时频分析,提取小波变换各层信号的能量与标准信号的能量之差组成特征向量;然后用FRVM对特征量进行分类,进而实现基于小波变换和FRVM的电能质量扰动分类新方法.实验仿真验证了该方法能够对各类电能质量扰动信号进行分类,并且其分类效率和准确率均优于传统的相关向量机分类方法.     

基于虚拟仪器和组态软件的船舶电能质量监控系统

船舶电力系统是一个独立的、完整的小型电力系统,对电能质量要求较高。为了实时监测船舶电网电能质量,基于虚拟仪器和组态软件开发一套电能质量监控系统。该系统采用DSP实时采集电能质量数据,数据分析和处理由LABVIEW软件完成,实现电压偏差、频率偏差、谐波、三相不平衡、电压波动等电能质量指标的计算和分析,最后,将电能质量关键数据通过OPC传送给船舶能量管理集控中心,对船舶电力系统进行统一能量管理提供数据支持。     

Experimental modeling and control design of shunt active power filters

One of the main issues when designing a control strategy for a power electronic system is the development of a reliable model of the real system. However, the evaluation of the actual plant parameters is difficult due to the mismatch between nameplate and actual values of components, and the presence of unmodeled dynamics and non-linearities. This paper presents a novel technique for both model parameters identification and optimized control design of a shunt active power filter system using genetic algorithms (GAs). Experimental results demonstrate that the proposed modeling and control design approach greatly improve the system performance.     

煤矿电能质量综合量化评价研究

根据煤矿用电负荷的特殊要求,定义了以最大负荷电流为基准的电流总畸变率,以及考虑负荷电流波形非正弦性的畸变功率因数;从电压质量、电流质量和功率因数3个方面确定电能质量分项指标,采用最小均方差法对电能分项指标进行筛选,建立了适用于煤矿供电系统的电能质量综合评价指标体系。运用熵权法计算不同指标的相对重要性,通过概率统计与模糊数学相结合的方法构建电能质量综合量化评价模型,实现对煤矿电网电能质量的分项计算和综合评价。实测数据分析结果验证了所构建的煤矿电能质量综合评价指标体系的合理性和评价方法的实用性。     

叠加暂态电能质量扰动的分形熵分析

暂态电能质量会给敏感用户带来重大损失,因此,在最普遍情况下识别叠加的暂态电能质量扰动非常重要。从图形模式识别的角度出发,基于分形理论对数据进行分段,并构建含扰动波形的能量熵,在此基础上通过最大熵方法辨识特征最为显著的扰动。随后在波形中去掉该扰动,在剩下的波形中辨识新的暂态扰动,由此可逐个辨识叠加波形中所有的暂态电能质量扰动。仿真实验表明,该算法具有较好的适应性及稳健性,可以在噪声环境中识别叠加的小幅度暂态电能质量扰动,识别率也较高。     

基于缓存辅助的全双工无线携能通信系统的中继选择策略

为了提高无线携能通信（SWIPT）系统的性能,构建了一个全新的基于缓存辅助的全双工中继协作系统模型,并在系统中考虑了空闲能量接入点（EAP）作为中继节点的额外能量补充。对于系统吞吐量最优化问题,提出一种基于功率分配协作的SWIPT中继选择策略。首先,基于通信服务质量与源节点发射功率等约束建立问题模型;其次,通过数学变换将原非线性混合整数规划问题转换为一对耦合优化问题;最后,利用KKT条件并借助拉格朗日函数解决内部优化问题,得到了功率分配因子和中继发射功率的闭式解,并在此结果上解决外部优化问题,选择最佳中继进行协作通信。仿真实验结果表明,空闲EAP和中继处高速缓冲存储器的配置具有可行性和有效性,并且,所提系统在吞吐量增益方面明显优于传统的中继协作通信系统。     

一种软启停正负双直流电源的设计

变形镜驱动器正负电源加电或者断电不同步,导致其在加电瞬间或者断电瞬间,输出端会输出一个-38.0V和86.0V的冲击电压,这个冲击电压使得变形镜在未开始工作时就产生了较为严重的面形畸变,为此研制了基于微处理器的软启停直流电源,它输出两路按一定时序变化的输出电压作为后续两个继电器的控制端,再通过这两个继电器分别控制变形镜驱动器正、负电源的导断,从而使得变形镜驱动器的正负电源同时加载或者卸载。在硬件平台了进行了实验验证,结果表明,使用软启停直流电源后,变形镜驱动器加电瞬间或断电瞬间,其产生的脉冲电压的峰-峰不超过0.45V,远远小于未使用软启停直流电源前的冲击电压,满足了系统的设计要求。     

Implementation and experimental studies of an adaptive self-optimizing power system stabilizer

This paper describes the implementation and experimental studies of an adaptive self-optimizing pole shifting power system stabilizer. Using an Intel iSBC386/21 single-board computer, the adaptive power system stabilizer has been tested on a physical model of a single-machine infinite-bus power system. Under different operating conditions and disturbances, the behavior of the proposed adaptive stabilizer was investigated. Comparison has also been made to a digital-type conventional fixed-parameter power system stabilizer. Results of the experimental studies show that the proposed adaptive stabilizer outperforms the conventional stabilizer.     

Power system model validation for power quality assessment applications using genetic algorithm

This paper presents an intelligent system for power quality assessment application. This system is used for power system model validation. A genetic algorithm (GA) based system for validating the power system model in capacitor switching studies has been developed. The problem formulation and the proposed solution are illustrated. The feasibility of the developed system for practical applications is demonstrated by evaluation studies.     

A cascade-type hierarchical fuzzy system with additional defuzzification of layers for the automatic power quality diagnosis

In general the power quality diagnosis of low-voltage electrical systems is a difficult issue due to the nuances of different power quality standards around the world and the uncertainties characteristics of the evaluation parameters. In this framework, this paper proposes a new methodology for diagnosing the power quality by means of a cascade-type hierarchical fuzzy system with additional defuzzification of layers (C-HFS-ADL), also proposed in this paper, which is able to evaluate the power quality indices in steady-state (total harmonic distortions, power factor, voltage variation, and unbalance voltage) considering several standards and provides a proper and complete diagnosis of the power quality in electrical systems. In the proposed C-HFS-ADL each output of a subsystem is transferred between inner layers of the hierarchical system and a total power quality diagnosis is obtained taking into account a secondary decision-making process with additional defuzzification in order to have a partial diagnosis for each subsystem of the hierarchy. In addition, an algorithm was implemented considering different inference systems for analyzing the behavior of the C-HFS-ADL on a database (power quality indices) obtained from a real electrical substation for observing its advantages and disadvantages.     

Optimization techniques for improving power quality data mining using wavelet packet based support vector machine

This paper aims at automatic classification of power quality events using Wavelet Packet Transform (WPT) and Support Vector Machines (SVM). The features of the disturbance signals are extracted using WPT and given to the SVM for effective classification. Recent literature dealing with power quality establishes that support vector machine methods generally outperform traditional statistical and neural methods in classification problems involving power disturbance signals. However, the two vital issues namely the determination of the most appropriate feature subset and the model selection, if suitably addressed, could pave way for further improvement of their performances in terms of classification accuracy and computation time. This paper addresses these issues through a classification system using two optimization techniques, the genetic algorithms and simulated annealing. This system detects the best discriminative features and estimates the best SVM kernel parameters in a fully automatic way. Effectiveness of the proposed detection method is shown in comparison with the conventional parameter optimization methods discussed in literature like grid search method, neural classifiers like Probabilistic Neural Network (PNN), fuzzy k-nearest neighbor classifier (FkNN) and hence proved that the proposed method is reliable as it produces consistently better results.     

电力系统变配用协同分级保护分析与应用研究

电力系统继电保护是保障电网安全稳定运行最重要的防线,电力系统能量传输网络根据功能的不同可以分为发、输、变、配、用等多个环节,各个部分均存在保护装置。当用户侧发生故障时,由于保护之间配置的不匹配,经常会出现越级跳闸的情况,导致故障扩大甚至造成电网的裂解。尤其是当前配电网高比例可再生能源渗透下对继电保护的协同分级配合提出了更高的要求,配电网的故障特征发生了明显的改变。本文在考虑分布式电源并网对电力系统变配用分级保护的影响的基础上,首先讨论逆变型分布式电源的运行特性,重点讨论了其控制方式和低电压穿越能力,其次分析分布式电源接入配电网故障特征,分上游、下游和相邻馈线分析分布式电源对电力系统继电保护的影响,尤其是变、配、用保护之间的协同配合问题,提出了低电压穿越矩阵、用户分支系数矩阵和分布式电源系数矩阵并给出了他们之间的相互关系公式。最后,针对提出的电力系统协同分级保护优化方法进行实例分析,证明了所提方法的有效性与科学性。     

提高AP1000核电厂厂用电供电可靠性的分析与探索

从影响AP1000核电厂厂用电供电可靠性的诸多因素出发,阐述了AP1000核电厂厂用电的构成及电气系统的主要特点。就如何提高AP1000核电厂厂用电供电可靠性进行了较全面的分析,对AP1000核电厂厂用电设计应对严重事故工况的措施进行了探索。