基于APID-RBF神经网络的光伏MPPT方法

针对光照强度急速变化和局部阴影时光伏发电系统最大功率点追踪响应速度慢、多峰值等问题,提出一种基于RBF神经网络与自适应PID控制相结合的控制方法。首先,采用RBF神经网络对环境的实时变化直接跟踪光伏最大功率点。然后,利用自适应PID的辅助修正,抑制光伏电池输出功率的波动。神经网络能提升在复杂环境下的跟踪速度,自适应PID能增强对神经网络误差的消除能力,提升跟踪精度。仿真结果表明,APIDRBF双控策略具有稳态性能高和控制精度高等优点,能有效提高光伏发电效率和稳定性。

基于Labview的模拟光伏MPPT研究

根据光伏电池的物理数学模型,以及基于Boost变换器稳态工作原理推导出来的光伏占空比扰动控制机理和扰动观察法控制流程,采用电压源串联电阻替代光伏电池板,并采用STC15W4K32S4单片机作为主控单元通过编程实现模拟光伏MPPT爬山法控制策略,采用Labview对模拟光伏的电压、电流的采样,通过Labview图形编程实现对模拟光伏系统工作状态和MPPT控制策略实施效果的实时直观呈现。实验结果表明,利用Labview强大的数据采集、处理、图形功能能够方便地把复杂系统状态和控制策略的实施效果实时直观地呈现出来,为光伏等系统的研究开发提供方便,对光伏控制器的研究设计具有实际意义。

基于分段控制的光伏全工况MPPT研究

光伏(PV)阵列输出特性随运行环境及自身工况的变化而变化.为满足不同工况下最大功率点跟踪(MPPT)控制需求,在对光伏阵列各工况下输出特性进行分析的基础上,提出了一种改进量子粒子群算法(QPSO)与扰动观察法相结合的MPPT分段控制方法.在跟踪控制初期,采用非一致性自适应变异DCWQPSO算法进行最大功率点全局搜索,使功率点快速收敛至最大功率点附近,提高跟踪速度;在跟踪控制后期,采用闭环模糊控制扰动观察法进行最大功率点局部搜索,提高跟踪精度.Matlab仿真结果表明,该分段控制方法在光伏阵列各工况下仅需0.32 s即可完成MPPT,并保持稳定,比其他控制方法具有更快的跟踪速度及更高的跟踪精度,可有效提高光伏发电效率.

基于拟合反演滑模方法的光伏系统MPPT控制

该文提出一种基于拟合优化的反演滑模控制的混合MPPT方案。该方案首先根据光伏发电系统的P-V特征曲线,使用3次插值函数来拟合最大功率点处的参考电压,然后基于参考电压以及反演滑模控制原理,设计相应的控制器并通过PWM调制控制占空比,使之在不同的环境条件下能迅速有效跟踪最大功率点。最后,通过Matlab/Simulink仿真验证所提出优化方案的有效性,并与其他经典方法进行对比分析。结果显示,该方法跟踪速度快、稳态功率波动小,跟踪性能优异。

基于Fuzzy-PI的直驱永磁风力发电系统MPPT控制

通过对模糊PI控制算法、MPPT算法分析,并对变流器的控制策略进行推导,提出基于Fuzzy-PI控制策略,确定机侧以转速的偏差及其微分为输入,交轴电流为输出,风机达到最大功率跟踪效果;网侧变流器采用电压外环、电流内环双闭环控制策略。通过Simulink系统仿真,结果表明模糊PI控制系统能实现发电机的最大功率跟踪和单位功率因数运行,控制效果优于传统的PI控制策略。

基于Boost变换器的D-PMSG风力发电系统MPPT控制

为了提高直驱永磁风力发电系统的最大功率点跟踪控制性能,通过对Boost占空比变化与风力机输出特性的关系分析,提出一种基于模糊梯度步长爬山搜索法,将风力机输出转速变化量和风力机输出功率变化量作为模糊控制器的输入量,Boost变换器的占空比作为模糊控制器的输出量,实现风力机最大功率点跟踪控制。建立了系统仿真模型并进行仿真验证,结果表明,模糊梯度步长爬山搜索法能实现直驱永磁风力发电系统的最大功率点跟踪控制,控制效果优于传统变步长爬山搜索算法。

Comparative assessment of maximum power point tracking procedures for photovoltaic systems

The fast growing demands and increasing awareness for the environment, PV systems are being rapidly installed for numerous applications.However, one of the important challenges in utilizing a PV source is the maximum power harnessing using various maximum power point tracking techniques available. With the large number of MPPT techniques, each having some merits and demerits, confusion is always there for their proper selection. Discussion on various proposed procedures for maximum power point tracking of photovoltaic array has been done. Based on different parameters analysis of MPPT techniques is carried out. This assessment will serve as a suitable reference for selection, understanding different ways and means of MPPT.

Overview of Maximum Power Point Tracking Control Methods for PV Systems

Maximum power point tracking (MPPT) controllers play an important role in photovoltaic systems. They maximize the output power of a PV array for a given set of conditions. This paper presents an overview of the different MPPT techniques. Each technique is evaluated on its ability to detect multiple maxima, convergence speed, ease of implementation, efficiency over a wide output power range, and cost of implementation. The perturbation and observation (P & O), and incremental conductance (IC) algorithms are widely used techniques, with many variants and optimization techniques reported. For this reason, this paper evaluates the performance of these two common approaches from a dynamic and steady state perspective.

复杂遮荫下基于改进GWO的光伏多峰MPPT控制

光伏阵列在复杂遮荫环境下的P-U曲线呈现多个峰值导致最大功率跟踪(MPPT)算法失效,为此提出双层控制模型,在上层模型中将Levy飞行和多项式变异策略嵌入灰狼算法,构建Levy-变异灰狼优化算法(LPGWO)搜索全局最大功率点;在下层模型中采用扰动观察法对最大功率点进行局部跟踪,进而有效降低复杂遮荫环境下的功率振荡。仿真结果表明,在多峰MPPT控制中,所提模型具有跟踪速度快、收敛精度高、整体功率振荡小等特点,能有效提升复杂遮荫环境下光伏阵列的最大功率跟踪效率和精度。

Variable Parameter Nonlinear Control for Maximum Power Point Tracking Considering Mitigation of Drive-train Load

Since mechanical loads exert a significant influence on the life span of wind turbines, the reduction of transient load on drive-train shaft has received more attention when implementing a maximum power point tracking(MPPT) controller.Moreover, a trade-off between the efficiency of wind energy extraction and the load level of drive-train shaft becomes a key issue. However, for the existing control strategies based on nonlinear model of wind turbines, the MPPT efficiencies are improved at the cost of the intensive fluctuation of generator torque and significant increase of transient load on drive train shaft. Hence, in this paper, a nonlinear controller with variable parameter is proposed for improving MPPT efficiency and mitigating transient load on drive-train simultaneously. Then,simulations on FAST(Fatigue, Aerodynamics, Structures, and Turbulence) code and experiments on the wind turbine simulator(WTS) based test bench are presented to verify the efficiency improvement of the proposed control strategy with less cost of drive-train load.

Maximum power point tracking of a photovoltaic energy system using neural fuzzy techniques

In order to improve the output efficiency of a photovoltaic （PV） energy system, the real-time maximum power point （MPP） of the PV array should be tracked closely. The non-linear and time-variant characteristics of the photovoltaic array and the non-linear and non-minimum phase characteristics of a boost converter make it difficult to track the MPP as in traditional control strategies. A neural fuzzy controller （NFC） in conjunction with the reasoning capability of fuzzy logical systems and the learning capability of neural networks is proposed to track the MPP in this paper. A gradient estimator based on a radial basis function neural network is developed to provide the reference information to the NFC. With a derived learning algorithm, the parameters of the NFC are updated adaptively. Experimental results show that, compared with the fuzzy logic control algorithm, the proposed control algorithm provides much better tracking performance.

Maximum Power Point Tracking Control Using Neural Networks for Stand-Alone Photovoltaic Systems

The employment of maximum power point tracking techniques in the photovoltaic power systems is well known and even of immense importance. There are various techniques to track the maximum power point reported in several literatures. In such context, there is an increasing interest in developing a more appropriate and effective maximum power point tracking control methodology to ensure that the photovoltaic arrays guarantee as much of their available output power as possible to the load for any temperature and solar radiation levels. In this paper, theoretical details of the work, carried out to develop and implement a maximum power point tracking controller using neural networks for a stand-alone photovoltaic system, are presented. Attention has been also paid to the command of the power converter to achieve maximum power point tracking. Simulations results, using Matlab/Simulink software, presented for this approach under rapid variation of insolation and temperature conditions, confirm the effectiveness of the proposed method both in terms of efficiency and fast response time. Negligible oscillations around the maximum power point and easy implementation are the main advantages of the proposed maximum power point tracking (MPPT) control method.

基于光伏MPPT采样电流的自适应变步长INC算法

针对传统电导增量INC(incremental conductance)算法在跟踪最大功率点的过程中无法兼顾跟踪速度与稳态精度的问题,以及传统变步长算法在光照变化时容易发生误判的问题,提出了一种新型的自适应变步长INC算法。光照强度变化较大时,利用负载曲线与I-V特性曲线的工作原理,在暂稳态和非稳态下都可以根据最大功率点跟踪MPPT(maximum power point tracking)采样电流的变化,自适应调节跟踪速度;光照强度变化较小时,能够根据输出电压与功率的变化自适应减小步长,提高稳态精度。追踪速度是传统算法的9.3倍,是现有变步长算法的4.2倍,有效减少了光照强度变化带来的功率损失。

基于改进黏菌优化算法的光伏MPPT方法

光伏阵列在局部遮荫的情况下会导致光伏系统输出的功率-电压曲线出现多个极值点,具有全局寻优能力的传统群体智能优化算法进行最大功率追踪(maximum power point tracking,MPPT),普遍存在收敛速度慢、易陷入局部最优等问题。该文提出了一种基于改进黏菌优化算法的控制方法。先采用正态分布初始化种群,增加种群的多样性。然后应用莱维飞行策略和螺旋搜索策略,提高算法的全局搜索能力,避免陷入局部最优。经仿真验证,与粒子群算法和普通黏菌算法相比,改进黏菌算法在跟踪速度、稳定性等方面均有更显著的效果。

Maximum Power Point Tracking Using the Incremental Conductance Algorithm for PV Systems Operating in Rapidly Changing Environmental Conditions

Maximum Power Point Tracking (MPPT) is an important process in Photovoltaic (PV) systems because of the need to extract maximum power from PV panels used in these systems. Without the ability to track and have PV panels operate at its maximum power point (MPP) entails power losses;resulting in high cost since more panels will be required to provide specified energy needs. To achieve high efficiency and low cost, MPPT has therefore become an imperative in PV systems. In this study, an MPP tracker is modeled using the IC algorithm and its behavior under rapidly changing environmental conditions of temperature and irradiation levels is investigated. This algorithm, based on knowledge of the variation of the conductance of PV cells and the operating point with respect to the voltage and current of the panel calculates the slope of the power characteristics to determine the MPP as the peak of the curve. A simple circuit model of the DC-DC boost converter connected to a PV panel is used in the simulation;and the output of the boost converter is fed through a 3-phase inverter to an electricity grid. The model was simulated and tested using MATLAB/Simulink. Simulation results show the effectiveness of the IC algorithm for tracking the MPP in PV systems operating under rapidly changing temperatures and irradiations with a settling time of 2 seconds.

基于改进鲸鱼优化算法的光伏发电系统MPPT控制研究

在局部阴影条件下,常规的最大功率点跟踪MPPT(maximum power point tracking)算法因含有容易陷入局部极值、跟踪精度低等弊端,使其无法及时、精确地跟踪光伏发电系统的最大功率点,因此,提出了一种基于改进型鲸鱼优化算法的光伏发电系统MPPT控制策略。首先,采用混沌映射初始化种群,增加种群的多样性。其次,通过引入非线性收敛因子使局部寻优能力和全局搜索能力达到均衡。最后,通过引入非线性时变的自适应权重使系统及时跳出局部最优解,并提高搜索的精度。经仿真验证,与粒子群优化算法、狮群优化算法、传统的鲸鱼优化算法等相比,改进的鲸鱼算法在跟踪速度、精度、稳定性等方面均有更显著的效果。

Maximum Power Point Tracking With Fractional Order High Pass Filter for Proton Exchange Membrane Fuel Cell

Proton exchange membrane fuel cell(PEMFC) is widely recognized as a potentially renewable and green energy source based on hydrogen. Maximum power point tracking(MPPT) is one of the most important working conditions to be considered. In order to improve the performance such as convergence and robustness under disturbance and uncertainty,a fractional order high pass filter(FOHPF) is applied for the MPPT controller design based on the traditional extremum seeking control(ESC). The controller is designed with integerorder integrator(IO-I) and low pass filter(IO-LPF) together with fractional order high pass filter(FOHPF), by substituting the normal HPF in the original ESC system. With this FOHPF ESC,better convergence and smoother performance are achieved while maintaining the robust specifications. First, tracking stability is discussed under the commensurate-order condition. Then,simulation results are included to validate the proposed new FOHPF ESC scheme under disturbance. Finally, comparison results between FOHPF ESC and the traditional ESC method are also provided.

Parasitic Effects on the Performance of DC-DC SEPIC in Photovoltaic Maximum Power Point Tracking Applications

This paper presents an analysis of the effect of parasitic resistances on the performance of DC-DC Single Ended Pri- mary Inductor Converter (SEPIC) in photovoltaic maximum power point tracking (MPPT) applications. The energy storage elements incorporated in the SEPIC converter possess parasitic resistances. Although ideal components significantly simplifies model development, but neglecting the parasitic effects in models may sometimes lead to failure in predicting first scale stability and actual performance. Therefore, the effects of parasitics have been taken into consideration for improving the model accuracy, stability, robustness and dynamic performance analysis of the converter. Detail mathematical model of SEPIC converter including inductive parasitic has been developed. The performance of the converter in tracking MPP at different irradiance levels has been analyzed for variation in parasitic resistance. The converter efficiency has been found above 83% for insolation level of 600 W/m2 when the parasitic resistance in the energy storage element has been ignored. However, as the parasitic resistance of both of the inductor has increased to 1 ohm, a fraction of the power managed by the converter has dissipated;as a result the efficiency of the converter has reduced to 78% for the same insolation profile. Although the increasing value of the parasitic has assisted the converter to converge quickly to reach the maximum power point. Furthermore it has also been observed that the peak to peak load current ripple is reduced. The obtained simulation results have validated the competent of the MPPT converter model.

基于类箕舌线的自适应变步长MPPT算法设计

为进一步提高光伏发电系统的稳定性和发电效率,使用最大功率点跟踪技术(MPPT)使输出功率最大化。对此提出一种基于类箕舌线的自适应变步长扰动观测法,该方法综合考虑跟踪速度、振荡幅度和计算复杂度等因素,分析了类箕舌线函数中参数α和β的不同取值对算法的影响。应用Matlab/Simulink分别在改变光照强度和温度两种情况下进行仿真,并与定步长扰动观测法进行对比。仿真结果表明,所提算法明显提高了跟踪速度,改善了靠近MPP时功率的振荡问题,相比于传统算法具有明显优越性。算法计算复杂度小,跟踪性能好,可应用于算力较小的MPPT控制器中。