New Improved Maximum Power Point Tracking Algorithm for Partially Shaded PV Systems

The paper presents new MPPT algorithm for partial shading of series connected PV cells/modules. In the shaded condition, there is a problem of decrease in the total output power of the PV system. The proposed algorithm aims to reduce this problem by active bypassing of the shaded cells. The algorithm senses the irradiance of each cell and performs calculation in order to decide if to actively bypass the shaded cell or not. Extensive simulation results proved that algorithm works and increases the output power under partial shading conditions. Furthermore, the algorithm becomes more efficient when the number of cells is increased.

A New Flower Pollination Algorithm Strategy for MPPT of Partially Shaded Photovoltaic Arrays

Photovoltaic(PV)systems utilize maximum power point tracking(MPPT)controllers to optimize power output amidst varying environmental conditions.However,the presence of multiple peaks resulting from partial shading poses a challenge to the tracking operation.Under partial shade conditions,the global maximum power point(GMPP)may be missed by most traditional maximum power point tracker.The flower pollination algorithm(FPA)and particle swarm optimization(PSO)are two examples of metaheuristic techniques that can be used to solve the issue of failing to track the GMPP.This paper discusses and resolves all issues associated with using the standard FPA method as the MPPT for PV systems.The first issue is that the initial values of pollen are determined randomly at first,which can lead to premature convergence.To minimize the convergence time and enhance the possibility of detecting the GMPP,the initial pollen values were modified so that they were near the expected peak positions.Secondly,in the modified FPA,population fitness and switch probability values both influence swapping between two-mode optimization,which may improve the flower pollination algorithm’s tracking speed.The performance of the modified flower pollination algorithm(MFPA)is assessed through a comparison with the perturb and observe(P&O)method and the standard FPA method.The simulation results reveal that under different partial shading conditions,the tracking time for MFPA is 0.24,0.24,0.22,and 0.23 s,while for FPA,it is 0.4,0.35,0.45,and 0.37 s.Additionally,the simulation results demonstrate that MFPA achieves higher MPPT efficiency in the same four partial shading conditions,with values of 99.98%,99.90%,99.93%,and 99.26%,compared to FPA with MPPT efficiencies of 99.93%,99.88%,99.91%,and 99.18%.Based on the findings from simulations,the proposed method effectively and accurately tracks the GMPP across a diverse set of environmental conditions.

Probabilistic Global Maximum Power Point Tracking Algorithm for Continuously Varying Partial Shading Conditions on Autonomous PV Systems

A photovoltaic (PV) string with multiple modules with bypass diodes frequently deployed on a variety of autonomous PV systems may present multiple power peaks under uneven shading. For optimal solar harvesting, there is a need for a control schema to force the PV string to operate at global maximum power point (GMPP). While a lot of tracking methods have been proposed in the literature, they are usually complex and do not fully take advantage of the available characteristics of the PV array. This work highlights how the voltage at operating point and the forward voltage of the bypass diode are considered to design a global maximum power point tracking (GMPPT) algorithm with a very limited global search phase called Fast GMPPT. This algorithm successfully tracks GMPP between 94% and 98% of the time under a theoretical evaluation. It is then compared against Perturb and Observe, Deterministic Particle Swarm Optimization, and Grey Wolf Optimization under a sequence of irradiance steps as well as a power-over-voltage characteristics profile that mimics the electrical characteristics of a PV string under varying partial shading conditions. Overall, the simulation with the sequence of irradiance steps shows that while Fast GMPPT does not have the best convergence time, it has an excellent convergence rate as well as causes the least amount of power loss during the global search phase. Experimental test under varying partial shading conditions shows that while the GMPPT proposal is simple and lightweight, it is very performant under a wide range of dynamically varying partial shading conditions and boasts the best energy efficiency (94.74%) out of the 4 tested algorithms.

Electrical Power Losses in a Photovoltaic Solar Cell Operating under Partial Shading Conditions

The aim of this paper is to determine the power losses recorded by a PV generator operating under partial shading conditions. These losses are evaluated through two distinct methods. The first method is based on mathematical modeling, while the second is based on Simulink’s physical model. The losses recorded are considerable and increase as a function of the increase in the percentage of shading up to a limit value where they become constant in the case where an ideal by-pass diode is connected in parallel with the modules. This limit value is non-existent in the case where the bypass diode is not ideal, which in fact corresponds to the real model. However, it emerges that the power losses are minimized in a PV system comprising bypass diodes, in particular in the case where the partial shading is considerable.

Development of Hybrid MPPT Algorithm for Maximum Power Harvesting under Partial Shading Conditions

In this paper, a Hybrid MPPT algorithm is proposed to improve the efficiency of photovoltaic (PV) systems under partial shading conditions. Partial shading occurs due to clouds, trees, dirt and dust in PV systems. In partial shading, multiple peaks arise in the PV characteristic curve. The Maximum power point tracking (MPPT) algorithm adjusts the duty cycle of the switch in DC-DC converter for regulating the input voltage at the Maximum power point (MPP) and to provide impedance matching i.e. input resistance of converter equal to equivalent solar resistance of PV system at MPP for the maximum power transfer. The Cuk converters have low switching losses and the highest efficiency. Therefore Cuk converter is chosen as power conditioning circuit to trackmaximum power using Hybrid MPPT technique. The influence of algorithm parameters on system behaviour is investigated and the various advantages and drawbacks of the technique are identified for different weather conditions. Practical results obtained using Solartech SPMO85P PV modules connected to a RL load through Hybrid MPPT controller validates the simulated results.

A Robust Single-Sensor MPPT Strategy for Shaded Photovoltaic-Battery System

A robust single-sensor global maximum power point tracking(MPPT)strategy based on modern optimization for photovoltaic systems considering shading conditions is proposed in this work.The proposed strategy is designed for battery charging applications and direct current(DC)microgrids.Under normal operation,the curve of photovoltaic(PV)output power versus PV voltage contains only a single peak point.This point can be simply captured using any traditional tracking method like perturb and observe.However,this situation is completely different during the shadowing effect where several peaks appear on the power voltage curve.Most of these peaks are local with only a single global.This condition leads to the incapability of traditional tracking approaches to extract the global peak power due to their inability to distinguish between the local and global peak points.They are trapped in the first peak point even when the point is local.Therefore,global tracking approaches based on modern optimization are highly required.A recent marine predators algorithm(MPA)has been used to solve the problem of tracking the global MPP under shadowing influence.Different shadowing scenarios are used to test and evaluate the performance of MPA based tracker.The obtained results are compared with particle swarm optimization(PSO)and ant lion optimizer(ALO).The results of the comparison con-firmed the effectiveness and robustness of the proposed global MPPT-MPA based tracker over PSO and ALO.

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.

A Novel Aquila Optimizer Based PV Array Reconfiguration Scheme to Generate Maximum Energy under Partial Shading Condition

This paper develops a real-time PV arrays maximum power harvesting scheme under partial shading condition(PSC)by reconfiguring PV arrays using Aquila optimizer(AO).AO is based on the natural behaviors of Aquila in capturing prey,which can choose the best hunting mechanism ingeniously and quickly by balancing the local exploitation and global exploration via four hunting methods of Aquila:choosing the searching area through high soar with the vertical stoop,exploring in different searching spaces through contour flight with quick glide attack,exploiting in convergence searching space through low flight with slow attack,and swooping through walk and grabbing prey.In general,PV arrays reconfiguration is a problem of discrete optimization,thus a series of discrete operations are adopted in AO to enhance its optimization performance.Simulation results based on 10 cases under PSCs show that the mismatched power loss obtained by AO is the smallest compared with genetic algorithm,particle swarm optimization,ant colony algorithm,grasshopper optimization algorithm,and butterfly optimization algorithm,which reduced by 4.34%against butterfly optimization algorithm.

基于改进黏菌算法的光伏多峰值MPPT控制

针对传统最大功率点跟踪技术在局部遮阴等天气条件下存在无法追踪到全局最大功率点的问题,提出一种基于改进黏菌算法的MPPT控制。首先,对太阳电池模型及多峰值特性进行分析;其次,在黏菌算法中引入领导者策略和基于最优个体的凸透镜反向学习策略,在提高算法计算精度、收敛速度的同时克服了算法易“早熟”现象;最后,根据光伏阵列最大功率输出特性分别确定算法优化模型、初始化位置及重启机制。仿真与实验结果表明:基于改进黏菌算法的MPPT控制能快速、准确地跟踪到全局最大功率点,有效规避陷入局部最优问题,提高了光伏系统的转换效率。

Partial Shading of PV System Simulation with Experimental Results

In a solar photovoltaic array, it is possible that shadow may fall over some of its cells. Under partial shading conditions the PV characteristic gets more complex with multiple peaks. The purpose of this paper is to illustrate, by analyzing different shading situations, the effects that partial shading can cause in a PV array. First this is done by simulation using Matlab/Simulink, then the impact of shading is illustrated experimentally by measurements on a two commercial 140 W PV panels series connected.

Maximum Power Point Tracking Using Fuzzy Logic Controller under Partial Conditions

This study proposes a fuzzy system for tracking the maximum power point of a PV system for solar panel. The solar panel and maximum power point tracker have been modeled using MATLAB/Simulink. A simulation model consists of PV panel, boost converter, and maximum power point tack MPPT algorithm is developed. Three different conditions are simulated: 1) Uniform irradiation;2) Sudden changing;3) Partial shading. Results showed that fuzzy controller successfully find MPP for all different weather conditions studied. FLC has excellent ability to track MPP in less than 0.01 second when PV is subjected to sudden changes and partial shading in irradiation.

基于改进混合算法的光伏多峰最大功率点跟踪

光伏阵列在局部遮阴下的输出具有多峰特性,且随工况变化而变化.针对传统的最大功率点跟踪(maximum power point tracking,简称MPPT)算法易陷入局部最优、跟踪时间较长,进而导致光伏发电效率低下的缺陷,提出局部遮阴下光伏多峰MPPT改进混合算法.该文算法包括最大功率点(maximum power point,简称MPP)前期全局搜索及后期局部搜索两部分.在MPP全局搜索阶段,采用惯性权重自适应调整的量子粒子群优化算法,将光伏阵列工作点移至MPP所在的单峰区间,在优化过程中对粒子群进行自适应t分布变异,引入禁忌搜索算法.在MPP局部搜索阶段,采用基于闭环模糊控制的变步长扰动观察法,将光伏阵列工作点快速精准调整至MPP.仿真结果表明:相对于其他4种算法,该文算法有更高的跟踪效率和跟踪精度,能更有效提高光伏发电效率.因此,该文算法具有优越性.

局部阴影下基于GWO-P&O混合算法的光伏最大功率点跟踪

针对局部遮阴环境下传统灰狼优化(Gray wolf optimization,GWO)算法在跟踪最大功率点时P-U特性曲线出现多峰值、后期收敛速度慢、稳态精度低等问题,结合灰狼优化算法和扰动观察法(Perturbation and observation,P&O)各自的优势,提出了基于GWO-P&O的混合优化最大功率点跟踪(Maximum power point tracking,MPPT)算法。首先,采用灰狼优化算法逐渐向光伏的全局最大功率点靠近。其次,在灰狼优化算法收敛后期引入P&O法,既保持了灰狼优化算法较高的稳态精度,又能以较快速度寻找到局部最大功率点。最后,在不同环境工况下,将所提出的GWO-P&O方法与传统GWO算法进行对比。结果表明,改进的GWO-P&O算法在保证良好稳态性能的同时,一定程度上提高了GWO算法后期跟踪最大功率时的收敛速度。

基于改进SCHO算法的局部遮荫光伏MPPT研究

针对局部遮荫工况下光伏阵列最大功率点跟踪(MPPT)存在的易陷入局部功率峰值点、跟踪时间长、跟踪精度低等问题,提出一种基于改进双曲正余弦优化(SCHO)的控制算法.其采用立方混沌映射初始化,提高初始候选解集的遍历性,并利用贝塔分布的概率特性修正SCHO算法的切换标准,提高算法与候选解集寻优进程的适配性.同时,对SCHO算法中的全局最优解、个体当前解引入平衡权重更新策略,且采用透镜成像反向学习策略对寻优后期的候选解进行扰动,采用比例收缩法对寻优空间进行动态钳位,提高算法的全局勘探及局部开发能力.Matlab仿真结果表明,相比其他控制算法,本文提出的改进SCHO算法能缩短MPPT时间、提高MPPT精度,故具有更优的MPPT性能,可为进一步提升光伏发电效率提供参考.

自适应免疫粒子群算法在光伏MPPT中的应用

光伏阵列在局部遮阴条件下,其P-U特性曲线呈多峰特性,传统的最大功率点跟踪(MPPT)算法容易陷入局部最优,而无法追踪到最大功率点。粒子群(PSO)算法适用于复杂多极值的寻优问题,因而在多峰值MPPT中得到广泛应用。针对粒子群算法寻优过程中易早熟收敛至局部最优、迭代后期收敛速度慢以及精度低等问题,提出了一种自适应免疫粒子群算法。该算法对惯性权重和学习因子进行自适应调整,并且与免疫算法相结合。仿真结果表明:该算法在静态局部遮阴以及动态局部遮阴条件下,均能追踪到最大功率点,并且收敛速度更快,精度更高,稳定性更好。

基于改进LGWO-INC算法的MPPT控制研究

光伏发电阵列板在局部遮阴下会产生多个功率峰值,传统算法难以准确快速追踪光伏最大功率点(maximum power point,MPP),该文提出一种基于莱维飞行灰狼算法(Levy grey wolf optimization,LGWO)与电导增量法(incremental conductance,INC)结合的复合算法追寻MPP,莱维飞行帮助灰狼算法跳出局部最优,搜寻MPP附近时,切换电导增量算法减少系统振荡,在静态与动态局部遮阴下通过Simulink进行光伏并网仿真验证。研究结果显示,所提复合算法收敛效果快速精确,并且符合并网谐波(total harmonic distortion,THD)含量要求,可保证系统的稳定运行。

Design of phase plates for shaping partially coherent beams by simulated annealing

Taking the Gaussian Schell-model beam as a typical example of partially coherent beams, this paper applies the simulated annealing （SA） algorithm to the design of phase plates for shaping partially coherent beams. A flow diagram is presented to illustrate the procedure of phase optimization by the SA algorithm. Numerical examples demonstrate the advantages of the SA algorithm in shaping partially coherent beams. An uniform flat-topped beam profile with maximum reconstruction error RE 〈 1.74% is achieved. A further extension of the approach is discussed.

利用改进布谷鸟优化算法的光伏全局MPPT方法

为了解决局部阴影下传统最大功率点追踪(maximum power point tracking, MPPT)算法容易陷入局部最优从而降低光伏系统发电效率的问题,本研究提出融合正弦余弦算法和自适应策略的布谷鸟优化算法(cuckoo search algorithm fusing sine cosine algorithm and adaptive strategy, AFCS),并应用于光伏全局MPPT控制中,以改善其收敛速度与追踪精度.设置多种光照情况,并与扰动观察法、花朵授粉算法和粒子群算法进行对比.经过Matlab/Simulink仿真验证,表明本算法拥有较快的收敛速度和较高的追踪精度,在各个光照条件下均能快速追踪到光伏阵列最大功率点,可以有效提高光伏系统的发电效率.

冠层下部遮荫和修枝对红锥苗木生长和光合特征的影响

为了解冠层下部枝叶遮荫和修枝对红锥(Castanopsis hystrix)的影响,以2年生红锥苗木为试材,在红锥苗木1/3冠层下部进行遮荫和修枝处理,测定红锥株高、地径、不同器官生物量和光合特征等指标,研究冠层下部遮荫和修枝对红锥苗木生长和光合特征的影响。结果表明,随遮荫度增加,株高和地径均呈先升后降的趋势;冠层上部和下部各部位生物量及总生物量均呈先升后降的趋势;冠层上部和下部叶生物量分配比及冠层上部茎和地上部分生物量分配比均呈先升后降的趋势;冠层下部枝条、茎和地上部分生物量分配比均呈下降趋势;冠层上部枝条和根生物量分配比及根冠比均呈先降后升的趋势;叶片净光合速率、气孔导度、蒸腾速率和水分利用效率均呈先升后降的趋势;胞间二氧化碳浓度呈先降后升的趋势。45%遮荫和修枝处理下,红锥苗木的生长指标、大部分器官生物量及其分配比和光合特征指标均较高,70%和85%遮荫处理下均较低。

基于定位收缩法的局部阴影条件下光伏最大功率点跟踪

光伏最大功率点跟踪是提高光伏发电效率的重要手段。在局部阴影条件下,光伏阵列的特性曲线呈现多峰形状,常规的传统算法容易陷入局部最优。如何在局部阴影条件下找到全局最大功率点(global maximum power point,GMPP)至关重要。提出了一种定位收缩法(locate and shrink algorithm,LSA),采用收缩边界的思想使得边界逐渐收缩到GMPP。LSA第一阶段提出了一种峰的定位方法,通过自适应采样结合I-V特性曲线能够定位主要峰的占空比范围。定位法能够与其他单峰算法结合,具有较强的扩展性。第二阶段提出了一种基于三点准则的收缩法,能够在单峰范围内通过收缩边界快速找到峰值点,并且具有很强的环境适应性。将LSA与多个算法进行仿真和硬件实验对比,结果表明LSA在跟踪速度、跟踪精度和稳态振荡方面有着明显优势。