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.

Performance enhancement of partially shaded solar PV array using novel shade dispersion technique

Solar photo voltaic array （SPVA） generates a smaller amount of power than the standard rating of the panel due to the partial shading effect. Since the modules of the arrays receive different solar irradiations, the P-V characteristics ofphotovoltaic （PV） arrays contain multiple peaks or local peaks. This paper presents an innovative method （magic square） in order to increase the generated power by configuring the modules of a shaded photo- voltaic array. In this approach, the physical location of the modules in the total cross tied （TCT） connected in the solar PV array is rearranged based on the magic square arrangement pattern. This connection is done without altering any electrical configurations of the modules in the PV array. This method can distribute the shading effect over the entire PV array, without concentrating on any row of modules and can achieve global peaks. For different types of shading patterns, the output power of the solar PV array with the proposed magic square configuration is compared with the traditional configurations and the performance is calculated. This paper presents a new reconfiguration technique for solar PV arrays, which increases the PV power under different shading conditions. The proposed technique facilitates the distribution of the effect of shading over the entire array, thereby, reducing the mismatch losses caused by partial shading. The theoretical calculations are tested through simulations in Matlab/ Simulink to validate the results. A comparison of power loss for different types of topologies under different types of shading patterns for a 4 × 4 array is also explained.

Maximum Power Point Tracking Technology for PV Systems: Current Status and Perspectives

Maximum power point tracking(MPPT)technology plays a key role in improving the energy conversion efficiency of photovoltaic(PV)systems,especially when multiple local maximum power points(LMPPs)occur under partial shading conditions(PSC).It is necessary to modify the operating point efficiently and accurately with the help of MPPT technology to maximize the collected power.Even though a lot of research has been carried out and impressive progress achieved for MPPT technology,it still faces some challenges and dilemmas.Firstly,the mathematical model established for PV cells is not precise enough.Second,the existing algorithms are often optimized for specific conditions and lack comprehensive adaptability to the actual operating environment.Besides,a single algorithm may not be able to give full play to its advantages.In the end,the selection criteria for choosing the suitable MPPT algorithm/converter combination to achieve better performance in a given scenario is very limited.Therefore,this paper systematically discusses the current research status and challenges faced by PV MPPT technology around the three aspects of MPPT models,algorithms,and hardware implementation.Through in-depth thinking and discussion,it also puts forward positive perspectives on future development,and five forward-looking solutions to improve the performance of PV systems MPPT are suggested.

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.

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.

State-of-the-art review of MPPT techniques for hybrid PV-TEG systems:modeling,methodologies,and perspectives

The development of alternative renewable energy technologies is crucial for alleviating climate change and promoting energy transformation.Of the currently available technologies,solar energy has promising application prospects owing to its merits of being clean,safe,and sustainable.Solar energy is converted into electricity through photovoltaic(PV)cells;however,the overall conversion efficiency of PV modules is relatively low,and most of the captured solar energy is dissipated in the form of heat.This not only reduces the power generation efficiency of solar cells but may also have a negative impact on the electrical parameters of PV modules and the service life of PV cells.To overcome the shortcomings,an efficient approach involves combining a PV cell with a thermoelectric generator(TEG)to form hybrid PV-TEG systems,which simultaneously improve the energy conversion efficiency of the PV system by reducing the operating temperature of the PV modules and increasing the power output by utilizing the waste heat generated from the PV system to generate electricity via the TEGs.Based on a thorough examination of the literature,this study comprehensively reviews 14 maximum power point tracking(MPPT)algorithms currently applied to hybrid PV-TEG systems and classifies them into five major categories for further discussion,namely conventional,mathematics-based,metaheuristic,artificial intelligence,and other algorithms.This review aims to inspire advanced ideas and research on MPPT algorithms for hybrid PV-TEG systems.

Research on the MPPT of Photovoltaic Power Generation Based on the CSA-INC Algorithm

The existing Maximum Power Point Tracking(MPPT)method has low tracking efficiency and poor stability.It is easy to fall into the Local Maximum Power Point(LMPP)in Partial Shading Condition(PSC),resulting in the degradation of output power quality and efficiency.It was found that various bio-inspired MPPT based optimization algorithms employ different mechanisms,and their performance in tracking the Global Maximum Power Point(GMPP)varies.Thus,a Cuckoo search algorithm(CSA)combined with the Incremental conductance Algorithm(INC)is proposed(CSA-INC)is put forward for the MPPT method of photovoltaic power generation.The method can improve the tracking speed by more than 52%compared with the traditional Cuckoo Search Algorithm(CSA),and the results of the study using this algorithm are compared with the popular Particle Swarm Optimization(PSO)and the Gravitational Search Algorithm(GSA).CSA-INC has an average tracking efficiency of 99.99%and an average tracking time of 0.19 s when tracking the GMPP,which improves PV power generation’s efficiency and power quality.

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 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.

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 Simple Primary Key Algorithm Based Shade Dispersion Method for Maximizing PV Power Generation under Partial Shading Conditions

The output power generation of a photovoltaic(PV)array reduces under partial shading,resulting in multiple local maxima in the PV characteristics and inaccurate tracking of the global maximum power point(GMPP).Various interconnection schemes are available to reduce power losses under partial shading.In this study,a primary key algorithm is proposed for distributing shading across an array.This method is suitable for any n×n PV array configuration and involves fewer calculations and variables,leading to reduced computational complexity.The power generations of a 9×9 PV array under four different shading conditions were compared with the configurations of:total cross-tied(TCT)and Su Du Ku,physical relocation and fixed column position of modules with fixed electrical connection(PRFCPM-FEC),and magic square(MS)and improved-odd-even-prime(IOEP).The advantage of the proposed method is that once the primary key elements are obtained,the remaining array elements are numbered in a simpler manner.The results obtained using the proposed arrangement show that the power is enhanced with reference to the TCT and is comparable to the Su Do Ku,PRFCPM-FEC,MS,and IOEP reconfigurations.

Optimal PV array reconfiguration under partial shading condition through dynamic leader based collective intelligence

This paper applies the innovative idea of DLCI to PV array reconfiguration under various PSCs to capture the maxi-mum output power of a PV generation system.DLCI is a hybrid algorithm that integrates multiple meta-heuristic algo-rithms.Through the competition and cooperation of the search mechanisms of different metaheuristic algorithms,the local exploration and global development of the algorithm can be effectively improved to avoid power mismatch of the PV system caused by the algorithm falling into a local optimum.A series of discrete operations are performed on DLCI to solve the discrete optimization problem of PV array reconfiguration.Two structures(DLCI-I and DLCI-II)are designed to verify the effect of increasing the number of sub-optimizers on the optimized performance of DLCI by simulation based on 10 cases of PSCs.The simulation shows that the increase of the number of sub-optimizers only gives a relatively small improvement on the DLCI optimization performance.DLCI has a significant effect on the reduction in the number of power peaks caused by PSC.The PV array-based reconstruction system of DLCI-II is reduced by 4.05%,1.88%,1.68%,0.99%and 3.39%,when compared to the secondary optimization algorithms.

A novel reconfiguration of the solar array to enhance peak power and efficiency under partial shading conditions:experimental validation

Non-homogeneous irradiation patterns and temperature levels immensely affect the performance of solar photovoltaic arrays.Partial shading conditions on solar arrays reduce the peak power and efficiency.This paper provides a new remedy called a novel Ramanujan reconfiguration(NRR)to eliminate this physical shading problem in solar photovoltaic systems.NRR is a static-based reconfigured technique that is built using a three-diode model with the help of the MATLAB®/Simulink®tool.The special feature of the proposed NRR technique is that when shade occurs on the solar modules,it gets realigned in a particular row,column,diagonal,corner,centre and middle peripheral cages.This helps over a wide range of shade dispersion on the solar array.The novel topology is tested against the conventional total cross-tied(TCT)model and recently introduced advanced reconfigured models,namely odd–even topology(OET)and Kendoku topology(KDT).The results are tested under certain shading conditions.The proposed NRR technique increases the peak power by 4.45,2.15 and 2.17 W under the first shading condition regarding TCT,OET and KDT.Its efficiency is improved by 0.51–2.18%under the third shading condition compared with other considered models in this study.In addition,NRR leads to smooth output curves under the second,third and fourth shading conditions,effectively mitigating the local power peaks.The experimental results show the proposed enhanced performance of the novel model against the other models.Graphical Abstract Remedy for physical problem correlated with solar photovoltaics Comparison with traditional and recent solar models Conclusion:NRR has effectively handled the problem related with solar models.It has improved the efficiency up to 31.44%under S4.Also,smooth output curves under S2-S4 shows its effectiveness in mitigating the local power peaks.Greater power gain at 3.94%under S4 is achieved by novel model.Real-time verification proves the supremacy of novel proposed model over other considered models in this work.

Novel Lyapunov-based rapid and ripple-free MPPT using a robust model reference adaptive controller for solar PV system

The technological,economic,and environmental benefits of photovoltaic(PV)systems have led to their wide-spread adoption in recent years as a source of electricity generation.However,precisely identifying a PV system’s maximum power point(MPP)under normal and shaded weather conditions is crucial to conserving the maximum generated power.One of the biggest concerns with a PV system is the existence of partial shading,which produces multiple peaks in the P–V characteristic curve.In these circumstances,classical maximum power point tracking(MPPT)approaches are prone to getting stuck on local peaks and failing to follow the global maximum power point(GMPP).To overcome such obstacles,a new Lyapunov-based Robust Model Reference Adaptive Controller(LRMRAC)is designed and implemented to reach GMPP rapidly and ripple-free.The proposed controller also achieves MPP accurately under slow,abrupt and rapid changes in radiation,temperature and load profile.Simulation and OPAL-RT real-time simulators in various scenarios are performed to verify the superiority of the proposed approach over the other state-of-the-art methods,i.e.,ANFIS,INC,VSPO,and P&O.MPP and GMPP are accomplished in less than 3.8 ms and 10 ms,respectively.Based on the results presented,the LRMRAC controller appears to be a promising technique for MPPT in a PV system.

Evaluation of series-parallel-cross-tied PV array configuration performance with maximum power point tracking techniques under partial shading conditions

Tracking the maximum power point is a critical issue with solar systems.The power output of the solar panel varies due to variations in irradiance and temperature.Nonuniform irradiation due to partial shading conditions has a direct impact on the characteristics of photovoltaic(PV)systems.To build a diversity of maximum power point tracking algorithms in solar PV systems,this work focuses on perturb and observe,incremental conductance,and fuzzy logic control methodologies.The suggested fuzzy logic control method outperformed the conventional incremental conductance and perturb and observe algorithms with a collection of 49 rules.This paper presents a novel series-parallel-cross-tied PV array configuration with a developed fuzzy methodology.To comment on the performance of a proposed system under various partial shading conditions,a series-parallel PV array configuration has been considered.The simulation result demonstrates that the fuzzy method has a percentage improvement in the global maximum power point tracking efficiency of 24.85%when compared to the perturb and observe method and a 65.5%improvement when compared to the incremental conductance method under long wide partial shading conditions.In the case of the middle partial shading condition,the fuzzy method has a percentage improvement in the global maximum power point tracking efficiency of 12.4%compared to the perturb and observe method and a 60.7%improvement compared to the incremental conductance method.

Maximum power point tracking of PV system under partial shading conditions through flower pollination algorithm

For maximum utilization of solar energy,photovoltaic(PV)power systems should be operated at the maximum power point(MPP)which can be achieved using maximum power point tracking(MPPT)methods.However,the occurrence of multi-peak on P-V curve of a PV array due to the changing environmental conditions such as being partially shaded increases the complexity of the tracking process.The global MPP cannot always be achieved by the conventional MPPT methods.Therefore a novel MPPT method for PV systems using flower pollination(FP)algorithm is proposed in this paper and the Levy flight is used to improve the convergence of FP algorithm.MPPT model of the PV system is established in MATLAB to verify the effectiveness of the proposed method,and the proposed method is compared with two well established MPPT methods.The simulation results indicate that the proposed MPPT method can quickly track the changes in external environment and effectively handle the partially shaded condition.

Hybrid, Optimal, Intelligent and Classical PV MPPT Techniques: A Review

Renewable energy-based solar photovoltaic(PV)generation is the best alternative for conventional energy sources because of its natural abundance and environment friendly characteristics.Maximum power extraction from the PV system plays a critical role in increasing the efficiency of the solar power generation during partial shading conditions(PSCs).Therefore,a suitable maximum power point tracking(MPPT)technique to track the maximum power point(MPP)is of high need,even under PSCs.This paper presents an organized and concise review of MPPT techniques implemented for the PV systems in literature along with recent publications on various hardware design methodologies.Their classification is done into four categories,i.e.classical,intelligent,optimal,and hybrid depending on the tracking algorithm utilized to track MPP under PSCs.During uniform insolation,classical methods are highly preferred as there is only one peak in the P-V curve.However,under PSCs,the F-V curve exhibits multiple peaks,one global maximum power point(GMPP)and remaining are local maximum power points(LMPP’s).Under the PSCs,classical methods fail to operate at GMPP and hence there is a need for more advanced MPPT techniques.Every MPPT technique has its advantages and limits,but a streamlined MPPT is drafted in numerous parameters like sensors required,hardware implementation,cost viability,tracking speed and tracking efficiency.This study provides the advancement in this area since some parameter comparison is made at the end of every classification,which might be a prominent base-rule for picking the most gainful sort of MPPT for further research.

Performance Investigation of Hybrid and Conventional PV Array Configurations for Grid-connected/Standalone PV Systems

Currently,the critical challenge in solar photovoltaic(PV)systems is to make them energy efficient.One of the key factors that can reduce the PV system power output is partial shading conditions(PSCs).The reduction in power output not only depends on a shaded region but also depends on the pattern of shading and physical position of shaded modules in the array.Due to PSCs,mismatch losses are induced between the shaded modules which can cause several peaks in the output power-voltage(P-V)characteristics.The series-parallel(SP),total-cross-tied(TCT),bridge-link(BL),honey-comb(HC),and triple-tied(TT)configurations are considered as conventional configurations,which are severely affected by PSCs and generate more mismatch power losses along with a greater number of local peaks.To reduce the effect of PSCs,hybrid PV array configurations,such as series-parallel:total-cross-tied(SP-TCT),bridge-link:total-cross-tied(BL-TCT),honey-comb:total-cross-tied(HC-TCT)and bridge-link:honey-comb(BL-HC)are proposed.This paper briefly discusses the modeling,simulation and performance evaluation of hybrid and conventional 7×7 PV array configurations during different PSCs in a Matlab/Simulink environment.The performance of hybrid and conventional PV configurations are evaluated and compared in terms of global maximum power(GMP),voltage and currents at GMP,open and short circuit voltage and currents,mismatch power loss(MPL),fill factor,efficiency,and a number of local maximum power peaks(LMPPs).

Maximum Power Enhancement Under Partial Shadings Using a Modified Sudoku Reconfiguration

Partial shading is one of the important factors in reducing maximum power generation from PV(Photovoltaic)arrays.Maximum power generation can be improved by selecting a PV array through a Total-Cross-Tied(T-C-T)connection.However,maximum power generated from T-C-T can still be improved by distribution of shading over various rows.Due to distribution of shading,the current entering the node increases and results in improved maximum power generation.This can be done effectively by using Sudoku reconfiguration techniques.These techniques are economical,since they don’t require any sensors and switching networks.This technique only changes the physical location of the PV panel but the electrical connection between the panels remains the same.This paper proposes a Modified Sudoku reconfiguration pattern which enhances the maximum power from the T-C-T connected PV array.Furthermore,the theoretical calculation of row current and power output have been done for existing and proposed topologies under various shading patterns.The performance of the proposed pattern has been analyzed and compared using specifications,such as Global Maximum Power(GMP),Fill Factor(FF),mismatch losses,and efficiency.From the results,it can be concluded that the Modified Sudoku reconfiguration enhances the GMP under all shading conditions.