This research proposes an improved Puma optimization algorithm(IPuma)as a novel dynamic recon-figuration tool for a photovoltaic(PV)array linked in total-cross-tied(TCT).The proposed algorithm utilizes the Newton-Raph...This research proposes an improved Puma optimization algorithm(IPuma)as a novel dynamic recon-figuration tool for a photovoltaic(PV)array linked in total-cross-tied(TCT).The proposed algorithm utilizes the Newton-Raphson search rule(NRSR)to boost the exploration process,especially in search spaces with more local regions,and boost the exploitation with adaptive parameters alternating with random parameters in the original Puma.The effectiveness of the introduced IPuma is confirmed through comprehensive evaluations on the CEC’20 benchmark problems.It shows superior performance compared to both established and modern metaheuristic algorithms in terms of effectively navigating the search space and achieving convergence towards near-optimal regions.The findings indicated that the IPuma algorithm demonstrates considerable statistical promise and surpasses the performance of competing algorithms.In addition,the proposed IPuma is utilized to reconfigure a 9×9 PV array that operates under different shade patterns,such as lower triangular(LT),long wide(LW),and short wide(SW).In addition to other programmed approaches,such as the Whale optimization algorithm(WOA),grey wolf optimizer(GWO),Harris Hawks optimization(HHO),particle swarm optimization(PSO),gravitational search algorithm(GSA),biogeography-based optimization(BBO),sine cosine algorithm(SCA),equilibrium optimizer(EO),and original Puma,the indicated method is contrasted to the traditional configurations of TCT and Sudoku.In addition,the metrics of mismatch power loss,maximum efficiency improvement,efficiency improvement ratio,and peak-to-mean ratio are calculated to assess the effectiveness of the indicated approach.The proposed IPuma improved the generated power by 36.72%,28.03%,and 40.97%for SW,LW,and LT,respectively,outperforming the TCT configuration.In addition,it achieved the best maximum efficiency improvement among the algorithms considered,with 26.86%,21.89%,and 29.07%for the examined patterns.The results highlight the superiority and competence of the proposed approach in both convergence rates and stability,as well as applicability to dynamically reconfigure the PV system and enhance its harvested energy.展开更多
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 algorith...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.展开更多
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 pose...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.展开更多
Weather variations present a major challenge for photovoltaic(PV)systems in obtaining the optimal output during maximum power point tracking(MPPT),particularly under partial shadowing conditions(PSCs).Bypass diodes ar...Weather variations present a major challenge for photovoltaic(PV)systems in obtaining the optimal output during maximum power point tracking(MPPT),particularly under partial shadowing conditions(PSCs).Bypass diodes are typically installed across the series-connected PV modules to avoid the occurrence of the hotspots.Consequently,the power curve exhibits several local peaks(LPs)and one global peak(GP).The conventional MPPTs typically become stuck in one of these LPs,presenting a significant decrease in both the power output and overall efficiency of the PV system.A major constraint of several optimization techniques is their inability to differ-entiate between the irradiancefluctuations and load alterations.In this study,we analyze seven different methods for MPPT.These include:the team game algorithm(TGA),social ki driver algorithm(SSD),differential evolution(DE),grey wolf optimization(GWO),particle swarm optimization(PSO),cuckoo search(CS),and the perturb and observe(P&O)method.These algorithms were applied in practice,and their effectiveness was experimentally demonstrated under different amounts of solar irradiation while maintain-ing a constant temperature.The results indicate that the CS and TGA approaches can accurately track the MPPT across various posi-tions on the P-V curve.These methods achieve average efficiencies of 99.59%and 99.54%,respectively.Additionally,the TGA achieves superior performance with the shortest average tracking time of 0.92 s,outperforming the existing MPPT algorithms.展开更多
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 cap...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.展开更多
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 mathe...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.展开更多
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 ...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.展开更多
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 ...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.展开更多
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 perform...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.展开更多
局部遮阴条件下光伏阵列的功率-电压特性曲线出现多个峰值,传统最大功率点跟踪(maximum power point tracking, MPPT)技术无法准确追踪到全局最大功率点。针对该问题提出一种基于改进算术优化算法(improved arithmetic optimization alg...局部遮阴条件下光伏阵列的功率-电压特性曲线出现多个峰值,传统最大功率点跟踪(maximum power point tracking, MPPT)技术无法准确追踪到全局最大功率点。针对该问题提出一种基于改进算术优化算法(improved arithmetic optimization algorithm, IAOA)的MPPT控制方法。首先,采用Sobol序列生成均匀分布的初始种群,增加种群多样性。其次,为了平衡算术优化算法(arithmetic optimization algorithm, AOA)的全局搜索和局部开发能力,对AOA中数学优化器加速函数的权重进行重构。最后,在AOA的位置更新中引入Lévy飞行策略,并将准反向学习用于每次更新后的最佳解,增强了算法的收敛速度和跳出局部最优的能力。仿真和实验结果表明,将改进后的算法应用于MPPT控制中,能够在不同的局部遮阴及光照突变条件下准确、快速地跟踪到全局最大功率点,且功率振荡小。展开更多
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 ...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.展开更多
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 ...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.展开更多
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 consi...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.展开更多
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...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.展开更多
光伏阵列在局部阴影条件下P-U曲线会出现多个峰值,传统的粒子群优化PSO(particle swarm optimization)算法无法快速精确地搜寻到最大功率点。针对这种情况,本文提出1种基于混沌映射和高斯扰动的改进粒子群优化算法最大功率点跟踪MPPT(ma...光伏阵列在局部阴影条件下P-U曲线会出现多个峰值,传统的粒子群优化PSO(particle swarm optimization)算法无法快速精确地搜寻到最大功率点。针对这种情况,本文提出1种基于混沌映射和高斯扰动的改进粒子群优化算法最大功率点跟踪MPPT(maximum power point tracking)控制策略。首先引入混沌Sine映射构造1种非线性随机递增惯性权重,并在粒子群的“个体认知”部分引入高斯扰动,同时利用对数函数构造学习因子,形成基于混沌映射和高斯扰动的改进粒子群算法;通过对6种典型单峰、多峰函数的测试,证明该算法收敛速度更快,不易陷入局部最优;将算法应用于MPPT控制中,并进一步通过不同算法MPPT控制进行对比仿真研究。对比仿真结果表明:在均匀光照强度、局部静态遮荫和动态遮荫3种情况下,基于混沌映射和高斯扰动的改进粒子群优化算法MPPT控制策略均具有更快的收敛速度和更小的搜索振荡幅度,能准确地搜寻到最大功率点,具有更高的寻优精度,从而提高了MPPT系统的发电效率。展开更多
基金funded by the Deanship of Scientific Research and Libraries,Princess Nourah bint Abdulrahman University,through the Program of Research Project Funding After Publication,grant No.(RPFAP-82-1445)。
文摘This research proposes an improved Puma optimization algorithm(IPuma)as a novel dynamic recon-figuration tool for a photovoltaic(PV)array linked in total-cross-tied(TCT).The proposed algorithm utilizes the Newton-Raphson search rule(NRSR)to boost the exploration process,especially in search spaces with more local regions,and boost the exploitation with adaptive parameters alternating with random parameters in the original Puma.The effectiveness of the introduced IPuma is confirmed through comprehensive evaluations on the CEC’20 benchmark problems.It shows superior performance compared to both established and modern metaheuristic algorithms in terms of effectively navigating the search space and achieving convergence towards near-optimal regions.The findings indicated that the IPuma algorithm demonstrates considerable statistical promise and surpasses the performance of competing algorithms.In addition,the proposed IPuma is utilized to reconfigure a 9×9 PV array that operates under different shade patterns,such as lower triangular(LT),long wide(LW),and short wide(SW).In addition to other programmed approaches,such as the Whale optimization algorithm(WOA),grey wolf optimizer(GWO),Harris Hawks optimization(HHO),particle swarm optimization(PSO),gravitational search algorithm(GSA),biogeography-based optimization(BBO),sine cosine algorithm(SCA),equilibrium optimizer(EO),and original Puma,the indicated method is contrasted to the traditional configurations of TCT and Sudoku.In addition,the metrics of mismatch power loss,maximum efficiency improvement,efficiency improvement ratio,and peak-to-mean ratio are calculated to assess the effectiveness of the indicated approach.The proposed IPuma improved the generated power by 36.72%,28.03%,and 40.97%for SW,LW,and LT,respectively,outperforming the TCT configuration.In addition,it achieved the best maximum efficiency improvement among the algorithms considered,with 26.86%,21.89%,and 29.07%for the examined patterns.The results highlight the superiority and competence of the proposed approach in both convergence rates and stability,as well as applicability to dynamically reconfigure the PV system and enhance its harvested energy.
文摘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.
文摘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.
基金supported by the Ministry of Higher Education(MOHE)of Malaysia through a research grant FRGS/1/2023/TK08/UNITEN/02/9.
文摘Weather variations present a major challenge for photovoltaic(PV)systems in obtaining the optimal output during maximum power point tracking(MPPT),particularly under partial shadowing conditions(PSCs).Bypass diodes are typically installed across the series-connected PV modules to avoid the occurrence of the hotspots.Consequently,the power curve exhibits several local peaks(LPs)and one global peak(GP).The conventional MPPTs typically become stuck in one of these LPs,presenting a significant decrease in both the power output and overall efficiency of the PV system.A major constraint of several optimization techniques is their inability to differ-entiate between the irradiancefluctuations and load alterations.In this study,we analyze seven different methods for MPPT.These include:the team game algorithm(TGA),social ki driver algorithm(SSD),differential evolution(DE),grey wolf optimization(GWO),particle swarm optimization(PSO),cuckoo search(CS),and the perturb and observe(P&O)method.These algorithms were applied in practice,and their effectiveness was experimentally demonstrated under different amounts of solar irradiation while maintain-ing a constant temperature.The results indicate that the CS and TGA approaches can accurately track the MPPT across various posi-tions on the P-V curve.These methods achieve average efficiencies of 99.59%and 99.54%,respectively.Additionally,the TGA achieves superior performance with the shortest average tracking time of 0.92 s,outperforming the existing MPPT algorithms.
基金supported by the Scientific Research Projects of Inner Mongolia Power(Group)Co.,Ltd.(Internal Electric Technology(2021)No.3).
文摘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.
文摘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.
文摘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.
基金supported by the Deanship of Scientific Research at Prince Sattam Bin Abdulaziz University under the research project No.2020/01/11742.
文摘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.
文摘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.
文摘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.
文摘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.
文摘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.
基金supported by the National Natural Science Foundation of China (Grant No 10574097)
文摘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.
文摘光伏阵列在局部阴影条件下P-U曲线会出现多个峰值,传统的粒子群优化PSO(particle swarm optimization)算法无法快速精确地搜寻到最大功率点。针对这种情况,本文提出1种基于混沌映射和高斯扰动的改进粒子群优化算法最大功率点跟踪MPPT(maximum power point tracking)控制策略。首先引入混沌Sine映射构造1种非线性随机递增惯性权重,并在粒子群的“个体认知”部分引入高斯扰动,同时利用对数函数构造学习因子,形成基于混沌映射和高斯扰动的改进粒子群算法;通过对6种典型单峰、多峰函数的测试,证明该算法收敛速度更快,不易陷入局部最优;将算法应用于MPPT控制中,并进一步通过不同算法MPPT控制进行对比仿真研究。对比仿真结果表明:在均匀光照强度、局部静态遮荫和动态遮荫3种情况下,基于混沌映射和高斯扰动的改进粒子群优化算法MPPT控制策略均具有更快的收敛速度和更小的搜索振荡幅度,能准确地搜寻到最大功率点,具有更高的寻优精度,从而提高了MPPT系统的发电效率。
