光伏组件精确工程模型及MPP电压范围研究

光伏并网变流器最大功率点(maximum power point,MPP)电压范围的确定是以组件的输出特性研究为基础的。组件的数学模型精确度较高,但涉及到超越方程,求解复杂且输入参数多,不适用于工程设计。简化模型计算过程简单但不能准确表述弱光条件下的组件输出特性。基于对数学模型及简化模型的对比分析,提出了一种精确的工程模型,该模型以数学模型为基准,对简化模型的补偿参数进行拟合修正,同时兼顾精确度与复杂程度。利用MATHCAD搭建仿真模型,将输出结果与数学模型输出进行对比,验证了精确工程模型的准确性。以该精确工程模型为基础,通过分析光照、温度等外界条件对MPP电压的影响,确定了并网变流器最大功率点跟踪工作电压范围,并通过实验验证了结论的正确性。

基于β参数的变步长MPPT控制研究

研究了当前光伏系统中最大功率点追踪技术(MPPT)的现状,针对传统MPPT方法在稳态性能与动态性能之间存在的矛盾,提出了一种改进的基于β参数的变步长算法。此算法基于对?-V曲线的分析,对光照强度的上升和下降采用两种不同大小的比例系数,从而在动态实现了快速追踪MPP并且避免了误判现象,同时,在稳态实现了零振荡。为了验证该算法的优越性,基于Matlab/Simulink平台对主要MPPT方法进行仿真分析,同时基于d SPACE和太阳能光伏阵列模拟器搭建实验样机并进行实验测试。仿真与实验结果验证了该算法的优越性,即能实现稳态零振荡及动态过程的快速跟踪。

基于ESO和分数阶PID的改进P&O控制策略

为了提高光伏电池转换效率、降低能量损失,有必要研究最大功率点跟踪(maximum power point tracking,MPPT)方法。针对传统扰动观察法(perturbation observation method,P&O)存在无法兼顾跟踪速度与稳态精度、在光照度发生较大变化时会产生误判现象的问题,文中提出一种能适应环境变化的变步长P&O控制策略。首先,利用光伏电池刚启动时类似恒流源的特性获取当前光照度下的短路电流,通过固定电流法推导出最大功率点(maximum power point,MPP)的参考电压;其次,当光照度突变时,提出功率修正方法,并给出突变时的变步长调整策略;最后,设计基于线性扩张状态观测器(linear extended state observer,LESO)的分数阶比例积分微分(fractional order proportion integration differentiation,FOPID)控制器,可以对算法输出的参考电压进一步进行跟踪补偿。仿真结果表明,所提控制策略可以提高稳态精度和跟踪速度,有效提高光伏电池的输出功率。

光伏发电系统最大功率点跟踪方法研究综述

在光伏发电系统中,为了提高光伏电池的利用效率,需要对光伏电池的最大功率点进行准确和快速的跟踪。阐述和评价了目前国内外出现的几种方法的原理和特点,对这几种方法进行了分析比较,最后探讨了最大功率点跟踪控制方法的发展思路,并对该领域今后的研究方向做了展望。

光伏阵列最大功率点跟踪控制方法综述

光伏发电系统的运行需要快速准确地进行最大功率点跟踪(MPPT),但目前很多最大功率点跟踪方法跟踪不够准确,从而导致了光伏系统的功率损失,为此综述了光伏阵列最大功率点跟踪的各种方法,包括日益成熟、改进和优化策略较多的扰动观察法和电导增量法,并总结了两种方法应用的局限性和需要注意的问题。从最大功率点跟踪的控制原理和发展历程出发,归纳了基于优化数学模型、扰动自寻优、智能处理方法及输出端控制等4类方法,分别说明了各种跟踪控制方法的优点和不足之处,并指出具体选择方法时需要统筹考虑跟踪方法实现的难易程度、经济成本、传感器类型、跟踪速度与精度的协调以及应用领域等各种因素。最后探讨了最大功率点跟踪控制方法的发展思路,对该领域今后的研究方向做了展望,指出单级式光伏逆变系统中的最大功率点跟踪己成为国内外光伏领域的一个研究热点。

一种引入停止机制的改进爬山算法

针对爬山法(hill-climbing searching,HCS)在最大功率点(maximum power point,MPP)处存在的转速振荡和风速变化导致搜索方向误判的问题,提出1种具有扰动停止机制的改进爬山算法。该算法不仅继承了变步长爬山法快速搜索至MPP附近的优点,还具有MPP检测和停止机制。在风机跟踪至MPP附近时,该机制不仅可以有效降低转速振荡对风机系统机械部件的磨损,而且克服了算法停止机制生效后风速再次变化时对搜索方向判断的干扰,从而进一步提高了风能捕获效率。在简化风电系统模型的基础上,仿真结果验证了该算法的有效性和优越性。

考虑随机阴影影响的光伏阵列失配运行特性

目前为了减少功率失配损失,一般太阳能模组串联时都配置旁路二极管以提供一个能量散逸的途径;而在并联运行前,还将配置阻断二极管以防止功率逆向传送。本文基于上述新配置条件重点考察了随机阴影导致的光伏阵列运行失配特性,并比较了不同串并联模式下的阵列抗失配能力。研究结果表明:由于多辐射强度导致功率曲线多峰走向的趋势,常规单调MPPT算法可能因只检测到伪极大值点而失效;其次,局部辐射强度导致的"门槛效应",即局部阴影的变化并不一定对全局功率输出有影响;最后,为了相对提高输出功率,提出全阵列设计时应优先考虑并联的建议。

光伏发电系统最大功率点跟踪方法研究综述

阐述和评价了目前国内外出现的几种方法的原理和特点,对这几种方法进行了分析比较,探讨了最大功率点跟踪控制方法的发展思路,并对该领域今后的研究方向做了展望。

基于fuzzy-PI双模控制的光伏发电系统最大功率点跟踪仿真研究

为了提高太阳电池阵列的工作效率和整个光伏发电系统的稳定性,在光伏发电系统中需要对光伏电池的最大功率点进行跟踪。为了消除常规模糊跟踪算法在最大功率点附近出现的振荡问题,在分析光伏电池伏安特性的基础上,提出了fuzzy-PI双模控制策略,分析了该控制算法的原理,并对控制系统做了设计。Matlab/Simulink仿真表明fuzzy-PI双模控制能够快速、准确地跟踪最大功率点,避免了最大功率点处的振荡,提高了系统稳定性和能量转换效率,从而使整个双模控制兼有了MPPT精确性与快速性。

光伏系统功率优化器研究与设计

为了确保太阳能电池工作在最大功率点(MPP),提高光伏阵列的转换效率,研制了一种光伏系统功率优化器,介绍了系统的组成结构与工作原理。设计了降压斩波电路(BUCK电路)、驱动电路和采集电路等系统模块电路,建立了光伏系统功率测试系统,于静态和动态2种环境下进行性能测试,实验结果由测试上位机软件实时显示,结果表明:系统跟踪MPP的效率为99.38%,在2种情况下均能够准确、实时地跟踪MPP,且系统稳定,检测结果精度较高。

光伏发电系统最大功率点跟踪控制的研究

针对扰动观察法的速度和精度在很大程度上受扰动初始值和扰动步长的影响,且在最大功率点附近存在功率振荡现象等问题,提出一种改进扰动观察法。首先当日照变化较快时,利用短路电流使输出功率能够快速跟踪在最大功率点附近,然后采用可变步长的扰动观察法使光伏电池稳定在最大功率点。通过仿真实验证明该改进方法明显缩短了最大功率点的跟踪时间,并且基本消除了功率振荡现象,提高了最大功率点跟踪控制技术。

基于SVM的光伏最大功率跟踪的预测研究

针对光伏组件中常用的最大功率跟踪方法存在的不足,将支持向量机用于预测光伏组件的最大功率点工作电压.支持向量机是一种新型的机器学习方法,该方法以结构风险最小化原则取代传统机器学习方法中的经验风险最小化原则,在小样本的机器学习中有着优异的性能.根据光伏组件的特点和最大功率点工作电压的影响因素,建立了支持向量机的最大功率点工作电压预测模型.实际仿真分析表明,与BP神经网络的模型相比,支持向量机的模型具有更高的预测精度.

变步长最大功率跟踪在双馈风力发电系统中的应用

在风力发电系统中,对于给定的风速达到最佳叶尖速比时,每条功率曲线均具有一个最大功率点(Maximum Power Point,MPP)。为了在不同的风速条件下均可产生最大的功率,必须对风力机的转速进行调节,以确保始终运行在最大功率点处。针对现有传统反馈控制的不足,提出了一种变步长最大功率跟踪策略,此方法可以根据输出功率变化的大小来改变扰动的步长值,克服了传统反馈控制成本高和固定步长的传统爬山算法稳定性、快速性难以兼顾的问题。同时采用定子电压定向控制,通过调节转子的励磁电流来调节定子发出的有功功率和无功功率。仿真实验结果证明了该方法的可行性。

染料敏化太阳电池光电极厚度的研究

根据电子在半导体中的扩散理论，建立了模拟染料敏化太阳电池（DSSC）J-V输出特性的数学模型。研究表明，随着光电极厚度（d）的增大，开路电压（VOC）下降：短路电流密度（JSC）先迅速增大。后缓慢减小：最大功率输出值MPP则先迅速增大，再迅速减小，表明d对DSSC光电转化效率影响显著。对DSSC的各参数进行了分析，发现操作参数，如光强、温度，对最佳电极厚度的确定没有影响，而物性参数，如光吸收系数、电子扩散系数及电子生命则决定了DSSC光电极厚度的大小。将模型结果与文献实验结果进行了对比，两者符合良好。说明模型结果可靠，可以为DSSC的优化设计提供理论依据。

分布式光伏发电系统最大功率点跟踪技术比较研究

基于当前光伏阵列最大功率点跟踪技术的研究现状,介绍了适用于分布式光伏发电系统最大功率点跟踪的各种常用控制方法,阐述了每一种控制方法的技术原理,分析和比较了这些常用控制方法的特点,总结了各自的优点和缺点,最后对分布式光伏发电系统最大功率点跟踪方法的选择问题进行了探讨,并指出了具体选择方法时应综合考虑的各种因素。

Experimental Analysis to Extract the Maximum Output of Serial and Parallel PV Module Configurations under Partial Shadow Conditions: A Case Study for Bambey, Senegal

Using an experimental setup, the series configurations (SC) and the parallel configurations (PC) of the PV cell connection are studied to compare their performance under the condition of partial shading s. The performance of the configurations is evaluated by comparing the open-circuit voltage, the short-circuit current, the maximum power point (MPP), the voltage and current corresponding to MPP, and the Fill Factor (FF). The variations of the series resistance and the shunt resistance of a PV module under different irradiance levels are also determined by considering the effect of thermal voltage. Finally, a comparison between the performance losses in the different configurations is presented. The results of this study show that the parallel configuration has the best performance under the conditions of partial shade in the context of this work.

Optimal PV Array Configuration for Extracting Maximum Power Under Partial Shading Conditions by Mitigating Mismatching Power Losses

The grid-connected or standalone PV central inverter architecture is comprised of several PV modules which are connected in different ways to form the PV array.The power generation capability of the PV array is primarily affected by partial shading conditions(PSC).Due to PSCs,the power output of the PV array is dramatically reduced,and mismatching losses are induced in the PV modules.Based on the extent of these problems,multiple peaks also appear in the power-voltage(P-V)curve,which makes it very difficult to track the global maximum power point(GMPP).The main objective of this research paper is to model and simulate the series(S),series-parallel(SP),bridge-link(BL),honey-comb(HC),total-cross-tied(TCT)and proposed triple-tied(TT)solar PV array configurations under various partial shading scenarios.The performance of all PV configurations is evaluated under a uniform approach,considering eight different shading scenarios.The performance of the considered PV configurations is analyzed in terms of their mismatching power losses,fill factors,efficiency,global maximum power points(GMPPs),local maximum power points(LMPPs),voltages and currents at GMPPs,open circuit voltage and short circuit currents.The above-mentioned PV configurations are modeled and simulated in a Matlab/Simulink environment by considering the KC-200GT module parameters.

A Two-stage Single-phase Grid-connected Solar-PV System with Simplified Power Regulation

This study focuses on the design and development of a simplified active power regulation scheme for a two-stage single-phase grid-connected solar-PV(SPV)system with maximum power point(MPP)estimation.It aims to formulate and test an improvised new control scheme to estimate the real-time MPP of the PV panel and operate only at either the MPP or on the right-hand side(RHS)of the PV characteristics of the panel.A simple active power regulatory control scheme was formulated to provide frequency control services to a single-phase grid without using an energy storage device.The plant operator provides the reserve fraction as the input for the active power regulation controller.At any time,the reserve fraction is used to determine the magnitude of the reference power to be extracted from the PV panel for injection into the grid.A simple PI controller was used to track the calculated reference power.The different modes of operation of the regulatory scheme are presented in detail.All the above control schemes are integrated and implemented through appropriate switching of the DC-DC converter alone.The DC-AC converter maintains the DC link voltage and unity power factor at the single-phase grid terminals.The proposed control schemes were tested on a 250 Wp solar panel feeding power to a 230 V,50 Hz single-phase grid through a two-stage converter.The entire scheme was modeled using the Matlab/Simulink platform,and the same was validated by hardware experimentation using Chroma Solar Simulator and NI myRIO controller under varied irradiation,temperature,and reserve fractions.The simulation and hardware results are compared and reported.

PV Array Reconfiguration Based on the Shaded Cells'Number for PV Modules

Reconfiguration can increase the output power for a PV array under partial shadows.However,traditional reconfiguration methods consider the PV module as either totally shaded or totally unshaded,and module-based simulation is employed to evaluate the reconfiguration effect.Actually,there is an unneglectable error when treating a partially shaded PV module as totally shaded,through using a more accurate cellbased simulation.Based on the analysis of the determinant factors on MPPs’power of a PV array,a new reconfiguration method is proposed based on the exact partial shadow shape projected on the PV array.This method restructures the electrical connection among PV modules of a PV array according to the shaded cells’number(SCN)of every PV module.Extensive cell-based simulations are carried out on a PV array to verify the effectiveness of the proposed SCN-based reconfiguration method.Comprehensive comparisons among various reconfiguration methods and shadow distributions clearly show its suitability to different irregular shadows and its superiority in PV output power enhancement.

Enhancement of grid-connected photovoltaic system using ANFIS-GA under different circumstances

In recent years, many different techniques are applied in order to draw maximum power from photo- voltaic （PV） modules for changing solar irradiance and temperature conditions. Generally, the output power generation of the PV system depends on the intermittent solar insolation, cell temperature, efficiency of the PV panel and its output voltage level. Consequently, it is essential to track the generated power of the PV system and utilize the collected solar energy optimally. The aim of this paper is to simulate and control a grid-connected PV source by using an adaptive neuro-fuzzy inference system （ANFIS） and genetic algorithm （GA） controller. The data are optimized by GA and then, these optimum values are used in network training. The simulation results indicate that the ANFIS-GA controller can meet the need of load easily with less fluctuation around the maximum power point （MPP） and can increase the convergence speed to achieve the MPP rather than the conventional method. Moreover, to control both line voltage and current, a grid side P/Q controller has been applied. A dynamic modeling, control and simulation study of the PV system is performed with the Matlab/Simulink program.