一种基于改进羊群算法的光伏系统最大功率跟踪策略

针对传统控制算法在局部遮蔽条件下无法持续准确地跟踪最大输出功率点,提出一种基于改进羊群算法的光伏系统最大功率跟踪策略.在羊群算法中引入扰动算子、反向种群和自适应放牧概率,以增强算法的局部开发能力,提高算法的寻优精度.均匀光照、局部遮蔽和变照度3种条件下的实验结果表明,改进羊群算法在不同环境条件下均能持续稳定地跟踪最大功率点,在收敛时间和收敛精度上均有较大优势,验证了该算法在最大功率点跟踪控制中的可行性.     

基于DSP的改进蚁群二阶段MPPT控制器设计

针对局部阴影条件下光伏阵列输出效率低并且对最大功率点跟踪MPPT(Maximum Power Point Tracking)收敛速度慢的问题,设计出一种基于DSP的智能MPPT控制器,提出一种目标因子与过渡机制的改进蚁群全局寻优二阶段MPPT全局寻优算法作,引入目标导向因子避免盲目寻优,引入过渡机制而弥补寻优末期的振荡完成最大功率跟踪,通过仿真与实验的 分析表明,改进后的算法在光照突变时具有较快的响应速度和较高的跟踪精度,避免系统趋于稳定时的功率振荡,提高了系统效率。     

基于改进粒子群算法的光伏最大功率点跟踪策略分析

阐述光伏电池最大功率点跟踪的问题，传统算法有容易陷入局部最优和收敛速度慢的特点，探讨利用天牛须搜索更新惯性权重并引入混沌扰动和“跳出”机制，对标准粒子群算法进行改进。将改进的粒子群算数法与标准粒子群算法在标准环境下仿真对比分析，改进的粒子群算法输出波动小，输出功率高。并应用改进的粒子群算法光照变化时进行最大功率点跟踪，验证算法有效性。     

基于细菌觅食算法的光伏阵列MPPT控制方法

针对光照不均匀条件下光伏阵列P-V输出特征呈现多波峰,传统算法无法摆脱局部最优值的缺点,提出了一种基于细菌觅食的优化算法,并首次应用于光伏阵列的最大功率点跟踪(MPPT)。算法引入了趋向性操作,用以进行局部范围内的最优寻找。分析了光伏阵列在遮挡条件下输出功率的变化特性,然后使用细菌觅食算法进行了最大功率点跟踪控制方法实验。实验表明,该算法能够成功摆脱局部最优值的约束,快速寻找到全局最大功率点,控制精度高,为光伏阵列最大功率点跟踪提供了一种新的实现方法。     

莱维飞行优化果蝇算法在光伏MPPT中的研究

实际工程中光伏阵列因局部遮挡引起局部阴影,造成输出的PU曲线呈现多峰值现象,传统方法进行最大功率点跟踪时,在跟踪精度、速度和最大功率点处振荡性都存在不足。为解决这些不足,在果蝇算法对多峰函数寻找最优解速度快的基础上,提出一种莱维飞行优化果蝇算法(LF-FOA)的光伏最大功率点跟踪策略。该方法以果蝇算法为主体,使用莱维飞行与果蝇算法相结合,增加其全局搜索能力,同时引入最劣解对果蝇运动步长进行修改,改进后的算法使果蝇以大小步长进行搜索,搜索的范围更加均匀,避免陷入局部寻优。通过函数仿真测试与Matlab/Simulink建模仿真,证明了LF-FOA算法能够逃离局部寻优,寻优时速度更快,精度更高,最大功率点处的振荡性更小。     

局部遮挡条件下的最大功率点跟踪

最大功率点跟踪(MPPT)算法在光伏发电系统中具有至关重要的作用,只有当光伏阵列工作在最大功率点时,才能将光伏阵列的利用率最大化。当光伏阵列受到外界灰尘、阴影等遮挡时,原来的单极值问题会转化为多极值问题,传统的MPPT算法可能收敛到局部最大值,而非全局最大值。本文在现有的MPPT算法上改进,提出了一种新的MPPT策略,将跟踪过程细分为4个阶段,针对每个阶段使用不同的跟踪算法。仿真实验证明,该方法既有处理多极值问题的能力,还有收敛速度快,无多点振荡的优点。     

局部遮挡条件下的光伏阵列最大功率点跟踪

针对局部遮挡条件下光伏阵列存在多个局部峰值的问题,以准确跟踪到光伏阵列的全局最大功率点为目标,提出一种新型的局部遮挡条件下光伏阵列最大功率点跟踪方法。首先深入分析了局部遮挡条件下的光伏阵列输出特性,并构建了相应的数学模型,然后采用改进扰动观察法搜索到全局最优的光伏阵列最大功率点,防止陷入局部最优点难题,最后采用Matlab 2014仿真软件对其性能进行分析。结果表明,本文方法可以快速、准确找到光伏阵列最大功率点,提高了光伏阵列的输出效率。     

部分遮挡下光伏组件MPPT技术研究

因云雾、植物、建筑等物体遮挡,或光伏器件本身的不一致性,可能导致多个功率极值出现,从而使传统的最大功率点跟踪方法失效。在光伏组件出现多功率极值的条件下,采用合理最大功率追踪算法,不陷入局部最大功率点,找到全局最大功率点值得研究。文中提出结合粒子群优化和常规最大功率点跟踪的复合算法,用于实现最大功率点跟踪,并与常规最大功率点跟踪算法进行仿真实验比较。以解决光伏组件工作在恶劣条件下的严重功率失配问题,提高光伏组件的能量转换率,保护光伏组件不受损坏。     

改进多元宇宙算法求解大规模实值优化问题

针对多元宇宙优化(MVO)算法中虫洞存在机制、白洞选择机制等不足,该文提出一种改进多元宇宙优化算法(IMVO)。设计固定概率的虫洞存在机制和前期快速收敛后期平缓收敛的虫洞旅行距离率,加快算法全局探索能力和快速迭代能力;提出黑洞的随机白洞选择机制,设计黑洞围绕白洞恒星进行公转并模型化,解决代间宇宙信息沟通的问题,中低维度数值比较实验验证了改进算法的优良性能。选取大规模实值问题较难优化的3个基准测试函数进行对比实验,改进算法在大规模优化问题上的求解精度和成功率方面具有较好的适用性和鲁棒性。     

基于粒子群优化算法的光伏阵列MPPT

针对光伏阵列在阴影下具有多个最大功率点,而传统的优化算法不能有效跟踪全局最大功率点的问题,提出了一种基于粒子群优化算法的跟踪算法,在Matlab平台上利用M函数对光伏阵列和跟踪算法进行编程。仿真结果表明:该控制算法不仅具有跟踪速动快、稳态精度高的特点,而且能够跟踪全局最大功率点,比传统的优化算法更有优势。     

A hybrid modified FA-ANFIS-P&O approach for MPPT in photovoltaic systems under PSCs

ABSTRACT

A modified firefly algorithm (MFO)-based adaptive neuro-fuzzy inference system (ANFIS) combined with the perturbation and observation (P&O) is used in this paper to track the maximum power point (MPP) in photovoltaic systems (PVs). The proposed method identifies and tracks the MPP in two stages. First, according to the irradiance on the solar panels, the ANFIS approximately identifies the MPP. In the second stage, the P&O method starts to act in the tracking cycle and initiates an accurate searching process from that point. The suggested hybrid method covers the problems of commonly-used methods, such as inability in detecting the global MPP under partial shading conditions (PSCs) and trapping in the local optima. Furthermore, the method provides significantly higher speed for the MPP tracking under various irradiance patterns. To prove the above-mentioned claims, the given approach is compared with the P&O method as a common method in the MPPT and particle swarm optimisation (PSO) which operates based on swarm intelligence. Simulation results obtained from MATLAB/Simulink environment show that the proposed method identifies and tracks the MPP under uniform irradiance and PSCs in a very short time of roughly 0.2 s.     

A PSO‐based maximum power point tracking for photovoltaic systems under environmental and partially shaded conditions

To increase the efficiency of photovoltaic (PV) systems, maximum power point (MPP) tracking of the solar arrays is needed. Solar arrays output power depends on the solar irradiance and temperature. Also the mismatch phenomenon caused by partial shade will affect the output power of solar systems and lead to the incorrect operation of conventional MPP tracker. Under partially shaded conditions, the solar array power–current characteristic has multiple maximum. This paper presents a maximum power point tracking (MPPT) with particle swarm optimization method for PV systems under partially shaded condition. The performance of the proposed method is compared with perturb and observe (P&O), improved P&O, voltage‐based maximum power point tracking and current‐based maximum power point tracking algorithms, especially, under partially shaded condition. Simulation results confirm that proposed MPPT algorithm with high accuracy can track the peak power point under different insolation, temperature and partially shaded conditions, and it has the best performance in comparison with four mentioned MPPT algorithms. Also under rapidly changing atmospheric conditions, the P&O algorithm is diverged. Copyright © 2013 John Wiley & Sons, Ltd.     

Experimental Performance of MPPT Algorithm for Photovoltaic Sources Subject to Inhomogeneous Insolation

Photovoltaic (PV) power system performance depends on local irradiance conditions. PV systems are sometimes subject to partial shading, which may produce a nonideal characteristic curve, presenting true and local power maxima in the P -I curve. Traditional maximum power point tracking (MPPT) algorithms can converge to local maximum, which is not the true MPP. In order to solve the problem, this paper investigates the effects of nonuniform solar irradiance distribution on a PV source. An MPPT algorithm that is able to optimize the source instantaneous operating power under nonuniform irradiance is proposed. The ability of the algorithm and its increased performance with respect to traditional algorithms are evaluated by means of experimental tests performed on a real PV power system.     

基于DSP的改进PSO光伏阵列MPPT控制应用

为了解决光伏（PV）系统在局部阴影条件下（PSC）的最大功率点跟踪问题,提出了一种基于改进粒子群算法（PSO）的快速最大功率点跟踪（MPPT）方法。与传统基于PSO的MPPT系统不同的是,采用了基于转换器电流动态行为的变量抽样时间策略（VSTS）,并且为了更快速的实现最大功率点跟踪,引入三个重要因数,即：粒子数、收敛速度以及抽样时间。采用DSP平台对提出系统进行了具体实现和性能评估,实验结果显示相比其他类似系统,在不同条件（包括PSC）下,提出算法均能够实现速度跟踪且精确度较高。     

An efficient GWO MPPT for a PV system using impedance information acceleration

This paper presents a novel maximum power point tracking (MPPT) method based on the grey wolf optimisation (GWO) technique for photovoltaic (PV) power generation systems. The proposed method utilises previous working duty cycles and their corresponding voltage and current data to compute the instantaneous DC impedance of a PV string. To determine the peak power characteristics of any PV string, the impedance variation of that PV string is used as an efficient shading factor. This shading factor simplifies the calculation of the GWO-MPPT algorithm to obtain multiple peak targets under partial shading conditions. Thus, the efficiency of the proposed power tracking technique can be improved considerably. The effectiveness of this method was validated through both simulation and hardware implementations. Results revealed that the search performance of five iterations of the proposed method was similar to that of ten iterations of a traditional GWO-MPPT method under normal conditions without shading. These results confirm the practicability of the proposed method in various applications.     

Maximum Power Point Tracking Scheme for PV Systems Operating Under Partially Shaded Conditions

Current-voltage and power-voltage characteristics of large photovoltaic (PV) arrays under partially shaded conditions are characterized by multiple steps and peaks. This makes the tracking of the actual maximum power point (MPP) [global peak (GP)] a difficult task. In addition, most of the existing schemes are unable to extract maximum power from the PV array under these conditions. This paper proposes a novel algorithm to track the global power peak under partially shaded conditions. The formulation of the algorithm is based on several critical observations made out of an extensive study of the PV characteristics and the behavior of the global and local peaks under partially shaded conditions. The proposed algorithm works in conjunction with a DC-DC converter to track the GP. In order to accelerate the tracking speed, a feedforward control scheme for operating the DC-DC converter is also proposed, which uses the reference voltage information from the tracking algorithm to shift the operation toward the MPP. The tracking time with this controller is about one-tenth as compared to a conventional controller. All the observations and conclusions, including simulation and experimental results, are presented.     

基于GA BPNN的MPPT控制方法与P&O的比较

针对传统光伏电池阵列控制方式在复杂天气环境下,对最大功率点跟踪效果不理想的现象。设计了一种基于GA BPNN的改进型恒压光伏MPPT控制算法,并通过搭建基于GA BPNN的改进型恒压光伏MPPT的仿真模型,再与传统P&O控制方法进行比较分析。仿真结果证明,该算法能准确快速地在复杂天气环境下进行最大功率点跟踪,且性能稳定。     

An enhanced scanning-based MPPT approach for DMPPT systems

In this paper, an improved maximum power point tracking (MPPT) approach being low parameter dependency, simple structure and limited search interval has been presented for distributed MPPT photovoltaic (PV) systems. Basically, this approach is based on scanning of power–voltage (P-V) characteristic curve of PV modules in a limited duty ratio interval which makes tracking operation simple, fast and efficiently available in both uniform irradiance and partial shading conditions (PSCs). By limiting the scanning interval of maximum and minimum values of duty ratio via some analyses related to P-V characteristic for PSCs, global MPPT (GMPPT) is achieved in an efficient way. So as to validate performance of the proposed approach, a single-ended primary inductance converter has been used in both simulation and experimental studies. PV simulator has been used as a PV source to obtain different module characteristics with different number of bypass diodes and PV power levels. Both simulation and experimental results clarify that improved MPPT approach realises GMPPT effectively. Due to the high performance results, this approach can be an alternative technique in module-integrated converters, smart modules and PV power optimisers in which single module is used.