Implementation of hybrid ANN–PSO algorithm on FPGA for harmonic estimation

Harmonic estimation is the main process in active filters for harmonic reduction. A hybrid Adaptive Neural Network–Particle Swarm Optimization (ANN–PSO) algorithm is being proposed for harmonic isolation. Originally Fourier Transformation is used to analyze a distorted wave. In order to improve the convergence rate and processing speed an Adaptive Neural Network Algorithm called Adaline has then been used. A further improvement has been provided to reduce the error and increase the fineness of harmonic isolation by combining PSO algorithm with Adaline algorithm. The inertia weight factor of PSO is combined along with the weight factor of Adaline and trained in Neural Network environment for better results. ANN–PSO provides uniform convergence with the convergence rate comparable that of Adaline algorithm. The proposed ANN–PSO algorithm is implemented on an FPGA. To validate the performance of ANN–PSO; results are compared with Adaline algorithm and presented herein.     

A novel approach for ANFIS modelling based on full factorial design

Adaptive neural network based fuzzy inference system (ANFIS) is an intelligent neuro-fuzzy technique used for modelling and control of ill-defined and uncertain systems. ANFIS is based on the input–output data pairs of the system under consideration. The size of the input–output data set is very crucial when the data available is very less and the generation of data is a costly affair. Under such circumstances, optimization in the number of data used for learning is of prime concern. In this paper, we have proposed an ANFIS based system modelling where the number of data pairs employed for training is minimized by application of an engineering statistical technique called full factorial design. Our proposed method is experimentally validated by applying it to the benchmark Box and Jenkins gas furnace data and a data set collected from a thermal power plant of the North Eastern Electric Power Corporation (NEEPCO) Limited. By employing our proposed method the number of data required for learning in the ANFIS network could be significantly reduced and thereby computation time as well as computation complexity is remarkably reduced. The results obtained by applying our proposed method are compared with those obtained by using conventional ANFIS network. It was found that our model compares favourably well with conventional ANFIS model.     

双频并网逆变器及其孤岛效应检测

提出一种用于分布式发电的双频并网逆变器,该逆变器由2个标准三相桥级联而成,其中一个桥工作在高频,提高输出电流性能;另一个桥工作在低频,主要输出功率,从而降低开关损耗,提高系统效率。为了检测孤岛效应,提出了基于dq变换和正反馈的新检测策略,基于该策略,提出了基于dq变换的电压正反馈和频率正反馈两种检测方法。两种方法具有无检测盲区、对电能质量影响小、检测速度快等优点。仿真结果表明,该逆变器输出电流与电网电压同相,总的谐波畸变率低,向电网输出的电能质量高。     

Direct Power Control of Dfig by Using Nonlinear Model Predictive Controller

This paper proposes a nonlinear model predictive direct power control (PDPC) strategy for a double fed induction generator (DFIG)‐based wind energy generation system. Active and reactive power variations of DFIG are calculated based on machine rules, and a nonlinear model of DFIG is given. A nonlinear model predictive controller (NMPC) is presented based on the useful cost function and constraint that it results in more proximity between simulations and reality. The power and current ripples are reduced and the optimal rotor voltage is generated based on an objective function and the constraints. The rotor voltage vector is calculated in the synchronous reference frame and transferred into the rotor reference frame. Simulation results of a 2 MW DFIG system show good performance of the proposed method during variation of active and reactive powers, machine parameters, and wind speed. Also, the transient responses of active and reactive powers are within a few milliseconds.     

Neural network based switching control of AC–AC converter with DC–AC inverter for voltage sags, harmonics and EMI reduction using hybrid filter topology

A neural network based AC–AC voltage restorer is designed for voltage sags and PWM type active power filter with compound trap passive filter as a new hybrid filter are simultaneously used for voltage harmonics compensation and electromagnetic interference (EMI) reduction. First objective is to apply the neural network based switching control technique for the AC–AC voltage restorer to reduce time delays during the switching conditions and switching losses. The aim of the IGBTs used in the AC–AC voltage restorer is to test and to find the best switching frequency–power combination in the steps of the simulation. Thus, the proposed AC–AC voltage restorer has important advantages such as fast switching response, simplicity and more intelligent structure, better output waveform. The transient condition of the AC–AC voltage restorer is improved via the neural network based control technique. The second objective is the proposed strategy for elimination of voltage harmonics using PWM type DC–AC inverter part of the system as an active power filter. The last objective of the system is EMI reduction with using hybrid filter and voltage restorer together. Three problems which are voltage sags, harmonics and EMI are solved with the proposed system simultaneously.     

ANFIS based multi-sector space vector PWM scheme for sensorless BLDC motor drive

This paper presents a design and development of Multi Sector Space Vector Pulse Width Modulation scheme (MS-SVPWM) for the speed control of brushless direct current (BLDC) motor drive. This control scheme is developed to enhance the performance of BLDC under wide range of speed and load variation. The hardware prototype is developed for 400 W, 30 V, 3000 rpm BLDC motor. The drive consists of uncontrolled rectifier unit for providing DC source to inverterunit. The proposed drive control has been done by implementing MS-SVPWM scheme using ANFIS control. The main function of ANFIS controller is to select the suitable sector for the drive and also predict the mismatching pulses by comparing conventional SVPWM and MS-SVPWM switching patterns. This new switching control technique helps to reduce switching losses of inverter and also improves an efficiency of BLDC system. This MS-SVPWM reduces the DC voltage ripple; Total Harmonic Distortion (THD) and torque ripple to the standard level. To verify and validate the practicality of the proposed system, the simulation is first performed using MATLAB Simulink tool. The hardware system is developed for the MS-SVPWM using DSPIC30F4011controller, the simulation and experimental results are presented.     

分布式可再生能源发电并网的无功优化研究

提出了基于杂交粒子群优化算法的分布式可再生能源并网的无功优化算法,从网损和静态电压稳定裕度两个角度出发,构建了含分布式发电系统的配电网无功优化的数学模型.在美国PG&E 69节点配电系统上进行效验.结果表明,该算法收敛性好、精度高;分布式电源并网后能有效降低系统的有功网损,提高电压稳定性,对分布式电源并网运行具有一定的...     

A new multi objective optimization approach based on TLBO for location of automatic voltage regulators in distribution systems

This paper proposes a new multi-objective optimization algorithm based on modified teaching–learning-based optimization (MTLBO) algorithm in order to solve the optimal location of automatic voltage regulators (AVRs) in distribution systems at presence of distributed generators (DGs). The objective functions including energy generation costs, electrical energy losses and the voltage deviation are considered in this paper. In the proposed MTLBO algorithm, teacher and learner phases are modified. The considered objective functions are energy generation costs, electrical energy losses and the voltage deviations. The proposed algorithm uses an external repository to save founded Pareto optimal solutions during the search process. Since the objective functions are not the same, a fuzzy clustering method is used to control the size of the repository. The proposed technique allows the decision maker to select one of the Pareto optimal solutions (by compromising) for different applications. The performance of the suggested algorithm on a 70-bus distribution network in comparison with other evolutionary methods such as genetic algorithm (GA), particle swarm optimization (PSO) and TLBO is extraordinary.     

柔性自激异步发电系统反演自适应滑模控制

为抑制宽转速范围条件下柔性自激异步发电系统(FS-CAGS)电压定向谐波干扰,提高FS-CAGS鲁棒稳定控制能力,实现功率快速跟踪控制,采用扩展卡尔曼滤波EKF电压定向与反演自适应滑模控制相结合的方法,提出一种EKF电压定向反演自适应滑模直接功率控制新方法.军用底盘集成式直流微电网中FS-CAGS控制仿真实验结果表明,在负载冲击扰动和宽转速突变条件下,相对于传统直接电压定向精确反馈线性化鲁棒控制方法,新控制方法可加快直流输出电压稳定速度,减小电压超调,提高功率跟踪速度,FS-CAGS电流谐波抑制和鲁棒稳定能力得到加强.     

Prediction of aerodynamics performance of continuously variable-speed wind turbine by adaptive neuro-fuzzy methodology

Horizontal-axis wind turbines (HAWT) have the constant rotor speed, while the blade tip speed changes continuously. This could reduce power performance of the wind turbine. In this paper, the accuracy of soft-computing technique was employed for aerodynamics performance prediction based on continuously variable-speed horizontal-axis wind turbine with optimal blades. The process, which simulates the $$\varphi$$ (relative wind angle), BEP (blade element parameter), SP (solidity parameter), CPtot (total power coefficient), CPl (local power coefficient), and CT (local thrust coefficient), with adaptive neuro-fuzzy inference system (ANFIS) was constructed. The inputs were local speed ratios λr and different values of drag-to-lift ratio ε. The performance of proposed system is confirmed by the simulation results. The ANFIS results are compared with the experimental results using root-mean-square error and coefficient of determination and Pearson’s coefficient. The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the ANFIS approach. The effectiveness of the proposed strategies is verified based on the simulation results.     

计及分布式电源的配电网电压波动特性研究

针对分布式电源出力的波动特性会使配电网发生电压波动变大等问题,在对分布式光伏和分布式风电输出功率特性进行分析的基础上,研究了分布式电源并网对配电网电压波动影响的相关原理;利用PSCAD/EMTDC电力系统仿真软件建立了包含分布式电源的配电网仿真实例模型。对配电网在不同容量、不同并网位置的分布式光伏和分布式风电作用下的电压波动情况进行仿真计算,获得了计及分布式电源的配电网电压波动特性相关规律。     

Harmonics elimination in multilevel inverter with unequal DC sources by fuzzy-ABC algorithm

The harmonious appearance in multilevel inverter output voltage is more for the case of unequal DC sources. In this paper, a hybrid technique incorporating fuzzy inference system (FIS) and artificial bee's colony (ABC) algorithm is proposed. FIS is a rule-based artificial intelligent technique which is used for generating the data set in terms of switching angle, harmonic voltage and harmonic distortion. The data set is generated as per the behaviour of the multilevel inverter without using any harmonic elimination technique. In the generated data set, the switching angle and the harmonic voltage are categorised as SMALL, MEDIUM and LARGE. Then, the ABC algorithm is used to optimise the selection of switching angles from the training data set. The performance of the proposed hybrid technique is tested on a 7-level cascade H-bridge inverter for different voltage levels of unequal DC sources using MATLAB/SIMULINK platform. The effectiveness and superiority of the proposed technique is evaluated by comparing the reduction capacity of total harmonic distortion for different voltage levels of unequal DC sources with particle swarm optimisation (PSO) algorithm and fuzzy-PSO algorithm.     

基于二阶滑模控制的变速双馈风力发电系统最大功率点跟踪

本文提出一种超螺旋二阶滑模控制方案同时实现双馈变速风力发电系统最大风能捕获和无功功率调节.通过设计两个二阶滑模控制器,实现控制目标,降低机械磨损,提高控制精度,通过调节发电机转子电压,跟踪风机最优转速和转子电流设定值,实现额定风速以下的最大风能捕获和无功功率调节.采用二次型李雅普诺夫函数确定控制参数范围、确保系统有限时间稳定性.1.5 MW风机系统仿真实验验证所提方案有效性.     

理想电网条件下双馈风力发电系统低电压穿越技术的控制策略研究

随着风电在电网所占比例的不断增大,提高风机在故障条件下的不间断运行能力越来越重要。通过分析交流励磁变速恒频双馈风机的运行特点,建立双馈风力发电系统的并网数学模型;针对电网电压小幅对称跌落,在不增加硬件成本的基础上,改进传统双馈发电机矢量控制策略,加入前馈补偿项来抑制电压小幅跌落时转子中的过电流,提高双馈风力发电系统的低压穿越能力。在MATLAB/SIMULINK中验证控制策略的合理性,为以后深入研究双馈风力发电系统提供了基础。     

基于地理信息系统的低压配电用户安全预警系统

针对目前偏远地区旅游景区配电设备常出现超负荷运行和火灾隐患的情况,本文基于地理信息系统设计了低压配电用户安全预警系统。研制了保护控制器并对各低压配电用户电气量、开关量及温度数据进行实时采集,将用户的地理位置和对应数据显示在系统中。系统对数据进行智能分析,可以实现用电安全与火灾隐患预警功能。该系统可以较好的适应旅游景区低压配电设备复杂的特点,提高低压配电网的可视化管理和信息化水平。     

基于混合算法的含分布式电源的配电网优化

考虑到分布式电源的选址与定容对配电网有着重要影响意义,针对分布式电源的接入对配电网系统能量损耗和各节点电压影响的问题,首先建立了以有功功率损耗和系统节点电压的目标函数优化模型,提出了充分整合引力搜索算法(GSA)的勘探能力和粒子群(PSO)的开采能力的混合算法(PSOG-SA),同时确定权重系数,最后采用IEEE-33标准节点配电网模型进行了仿真实验,通过和其他两种算法的比较,验证了配电网系统在该算法下的有效性和可靠性.算例分析表明,合理的DG接入能够一定程度上降低系统有功功率损耗,改善节点电压.     

Fixed frequency sliding mode control of renewable energy resources in DC micro grid

The rising cost of fossil fuels, their high depleting rate and issues regarding environmental pollution have brought the attention of the researchers towards renewable energy technologies. Different renewable energy resources like wind turbines, fuel cells and solar cells are connected to DC micro grid through controllable power electronic converters. In presence of these diverse generation units, robust controllers are required to ensure good power quality and to regulate grid voltage. This paper presents a sliding mode control based methodology to address the above mentioned challenges. The proposed technique keeps the switching frequency constant so that electromagnetic compatibility (EMC) issues can be solved with conventional filter design. Parallel operation of converter in DC micro gird is considered. Chattering reduction and power quality improvement by harmonic cancellation is proposed. A scaled down hardware for unregulated 11.5 V to 17.5 V input and 24V output is designed and tested. The experimental results show good performance of the controller under different loads and uncertain input voltage conditions. Moreover, the results show the robustness of the closed loop system to sudden variations in load conditions. Furthermore, a significant improvement in power quality is achieved by harmonic cancellation of chattering in the output of the converters.     

Modeling and simulation of static loads for wind power applications

This study aims to model and simulate static nonlinear loads with wind power generation to evaluate the impact of load models on wind power systems. Nonlinear loads are modeled as exponential load model, ZIP load model and combination of exponential/ZIP with an induction motor. The wind power generator is represented with a reduced-order doubly fed induction generator (DFIG) model. Developed models have been implemented in a grid-integrated wind power plant and simulated in MATLAB/SIMULINK. The effects of nonlinear loads into wind power plant are investigated in terms of bus voltages, angular speed, electrical torque, and d–q stator axes currents. Additional analyses are conducted to compare the behaviors of full- and reduced-order DFIG models under a selected loading condition. The results of this study indicate that the response of a system with DFIG is dependent of the load modeling and reduced-order DFIG model shows more stable trend than full-order DFIG model.     

Short-term wind speed forecasting based on a hybrid model

Wind power is currently one of the types of renewable energy with a large generation capacity. However, operation of wind power generation is very challenging because of the intermittent and stochastic nature of the wind speed. Wind speed forecasting is a very important part of wind parks management and the integration of wind power into electricity grids. As an artificial intelligence algorithm, radial basis function neural network (RBFNN) has been successfully applied into solving forecasting problems. In this paper, a novel approach named WTT–SAM–RBFNN for short-term wind speed forecasting is proposed by applying wavelet transform technique (WTT) into hybrid model which hybrids the seasonal adjustment method (SAM) and the RBFNN. Real data sets of wind speed in Northwest China are used to evaluate the forecasting accuracy of the proposed approach. To avoid the randomness caused by the RBFNN model or the RBFNN part of the hybrid model, all simulations in this study are repeated 30 times to get the average. Numerical results show that the WTT–SAM–RBFNN outperforms the persistence method (PM), multilayer perceptron neural network (MLP), RBFNN, hybrid SAM and RBFNN (SAM–RBFNN), and hybrid WTT and RBFNN (WTT–RBFNN). It is concluded that the proposed approach is an effective way to improve the prediction accuracy.     

分布式发电系统并网影响研究综述

针对分布式发电系统的多样性,对在实际电网中应用的分布式发电系统的特点及其发展动态进行了综述。从分布式发电系统并网运行的角度,重点分析了分布式发电系统的接入对地区电网的频率、电压、电能质量、潮流、电网损耗、电网调度、继电保护、可靠性、电力市场等方面产生的显著影响,充分说明妥善解决好并网运行影响,将是分布式发电健康快速发展的关键,对于我国能源结构调整、实现可持续发展具有重要现实意义。