This paper proposes a fingerprint matching method integrating transfer learning and online learning to tackle the challenges of environmental adaptability and dynamic interference resistance in photovoltaic(PV)array D...This paper proposes a fingerprint matching method integrating transfer learning and online learning to tackle the challenges of environmental adaptability and dynamic interference resistance in photovoltaic(PV)array DC arc fault location methods based on electromagnetic radiation(EMR)signals.Initially,a comprehensive analysis of the time–frequency characteristics of series arc EMR signals is carried out to pinpoint effective data sources that reflect fault features.Subsequently,a multi-kernel domain-adversarial neural network(MKDANN)is introduced to extract domain-invariant features,and a feature extractor designed specifically for fingerprint matching is devised.To reduce inter-domain distribution differences,a multi-kernel maximum mean discrepancy(MK-MMD)is integrated into the adaptation layer.Moreover,to deal with dynamic environmental changes in real-world situations,the support-class passive aggressive(SPA)algorithm is utilized to adjust model parameters in real time.Finally,MKDANN and SPA technologies are smoothly combined to build a fully operational fault location model.Experimental results indicate that the proposed method attains an overall fault location accuracy of at least 95%,showing strong adaptability to environmental changes and robust interference resistance while maintaining excellent online learning capabilities during model migration.展开更多
Conventional concentrator photovoltaics(CPV)face a persistent trade-off between high efficiency and high cost,driven by expensive multi-junction solar cells and complex active cooling systems.This study presents a com...Conventional concentrator photovoltaics(CPV)face a persistent trade-off between high efficiency and high cost,driven by expensive multi-junction solar cells and complex active cooling systems.This study presents a computational investigation of a novel Multi-Focal Pyramidal Array(MFPA)-based CPV system designed to overcome this limitation.The MFPA architecture employs a geometrically optimized pyramidal concentrator to distribute concen-trated sunlight onto strategically placed,low-cost monocrystalline silicon cells,enabling high efficiency energy capture while passively managing thermal loads.Coupled optical thermal electrical simulations in COMSOL Multiphysics demonstrate a geometric concentration ratio of 120×,with system temperatures maintained below 110℃ under standard 1000 W/m2 Direct Normal Irradiance(DNI).Ray tracing confirms 95%optical efficiency and a concentrated light spot radius of 2.48 mm.Compared with conventional CPV designs,the MFPA improves power-per-cost by 25%and reduces tracking requirements by 50%owing to its wide±15°acceptance angle.These results highlight the MFPA’s potential as a scalable,low-cost,and energy-efficient pathway for expanding solar power generation.展开更多
In order to address the challenges posed by complex background interference,high miss-detection rates of micro-scale defects,and limited model deployment efficiency in photovoltaic(PV)module defect detection,this pape...In order to address the challenges posed by complex background interference,high miss-detection rates of micro-scale defects,and limited model deployment efficiency in photovoltaic(PV)module defect detection,this paper proposes an efficient detection framework based on an improved YOLOv11 architecture.First,a Re-parameterized Convolution(RepConv)module is integrated into the backbone to enhance the model’s sensitivity to fine-grained defects—such as micro-cracks and hot spots—while maintaining high inference efficiency.Second,a Multi-Scale Feature Fusion Convolutional Block Attention Mechanism(MSFF-CBAM)is designed to guide the network toward critical defect regions by jointly modeling channel-wise and spatial attention.This mechanism effectively strengthens the specificity and robustness of feature representations.Third,a lightweight Dynamic Sampling Module(DySample)is employed to replace conventional upsampling operations,thereby improving the localization accuracy of small-scale defect targets.Experimental evaluations conducted on the PVEL-AD dataset demonstrate that the proposed RMDYOLOv11 model surpasses the baseline YOLOv11 in terms of mean Average Precision(mAP)@0.5,Precision,and Recall,achieving respective improvements of 4.70%,1.51%,and 5.50%.The model also exhibits notable advantages in inference speed and model compactness.Further validation on the ELPV dataset confirms the model’s generalization capability,showing respective performance gains of 1.99%,2.28%,and 1.45%across the same metrics.Overall,the enhanced model significantly improves the accuracy of micro-defect identification on PV module surfaces,effectively reducing both false negatives and false positives.This advancement provides a robust and reliable technical foundation for automated PV module defect detection.展开更多
Accurate estimation of photovoltaic(PV)parameters is essential for optimizing solar module perfor-mance and enhancing resource efficiency in renewable energy systems.This study presents a process innovation by introdu...Accurate estimation of photovoltaic(PV)parameters is essential for optimizing solar module perfor-mance and enhancing resource efficiency in renewable energy systems.This study presents a process innovation by introducing,for the first time,the Triangulation Topology Aggregation Optimizer(TTAO)integrated with parallel computing to address PV parameter estimation challenges.The effectiveness and robustness of TTAO are rigorously evaluated using two standard benchmark datasets(KC200GT and R.T.C.France solar cells)and a real-world dataset(Poly70W solar module)under single-,double-,and triple-diode configurations.Results show that TTAO consistently achieves superior accuracy by producing the lowest RMSE values and faster convergence compared to state-of-the-art metaheuristic algorithms.In addition,the integration of parallel computing significantly enhances computational efficiency,reducing execution time by up to 85%without compromising accuracy.Validation using real-world data further demonstrates TTAO’s adaptability and practical relevance in renewable energy systems,effectively bridging the gap between theoretical modeling and real-world implementation for PV system monitoring and optimization,contributing to climate mitigation through improved solar energy performance.展开更多
Accurate parameter extraction of photovoltaic(PV)models plays a critical role in enabling precise performance prediction,optimal system sizing,and effective operational control under diverse environmental conditions.W...Accurate parameter extraction of photovoltaic(PV)models plays a critical role in enabling precise performance prediction,optimal system sizing,and effective operational control under diverse environmental conditions.While a wide range of metaheuristic optimisation techniques have been applied to this problem,many existing methods are hindered by slow convergence rates,susceptibility to premature stagnation,and reduced accuracy when applied to complex multi-diode PV configurations.These limitations can lead to suboptimal modelling,reducing the efficiency of PV system design and operation.In this work,we propose an enhanced hybrid optimisation approach,the modified Spider Wasp Optimization(mSWO)with Opposition-Based Learning algorithm,which integrates the exploration and exploitation capabilities of the Spider Wasp Optimization(SWO)metaheuristic with the diversityenhancing mechanism of Opposition-Based Learning(OBL).The hybridisation is designed to dynamically expand the search space coverage,avoid premature convergence,and improve both convergence speed and precision in highdimensional optimisation tasks.The mSWO algorithm is applied to three well-established PV configurations:the single diode model(SDM),the double diode model(DDM),and the triple diode model(TDM).Real experimental current-voltage(I-V)datasets from a commercial PV module under standard test conditions(STC)are used for evaluation.Comparative analysis is conducted against eighteen advanced metaheuristic algorithms,including BSDE,RLGBO,GWOCS,MFO,EO,TSA,and SCA.Performance metrics include minimum,mean,and maximum root mean square error(RMSE),standard deviation(SD),and convergence behaviour over 30 independent runs.The results reveal that mSWO consistently delivers superior accuracy and robustness across all PV models,achieving the lowest RMSE values of 0.000986022(SDM),0.000982884(DDM),and 0.000982529(TDM),with minimal SD values,indicating remarkable repeatability.Convergence analyses further show that mSWO reaches optimal solutions more rapidly and with fewer oscillations than all competing methods,with the performance gap widening as model complexity increases.These findings demonstrate that mSWO provides a scalable,computationally efficient,and highly reliable framework for PV parameter extraction.Its adaptability to models of growing complexity suggests strong potential for broader applications in renewable energy systems,including performance monitoring,fault detection,and intelligent control,thereby contributing to the optimisation of next-generation solar energy solutions.展开更多
We present a computer-modeling framework for photovoltaic(PV)source emulation that preserves the exact single-diode physics while enabling iteration-free,real-time evaluation.We derive two closed-form explicit solvers...We present a computer-modeling framework for photovoltaic(PV)source emulation that preserves the exact single-diode physics while enabling iteration-free,real-time evaluation.We derive two closed-form explicit solvers based on the Lambert W function:a voltage-driven V-Lambert solver for high-fidelity I–V computation and a resistance-driven R-Lambert solver designed for seamless integration in a closed-loop PV emulator.Unlike Taylor-linearized explicit models,our proposed formulation retains the exponential nonlinearity of the PV equations.It employs a numerically stable analytical evaluation that eliminates the need for lookup tables and root-finding,all while maintaining limited computational costs and a small memory footprint.The R-Lambert model is integrated into a buck-converter emulator equipped with a discrete PI regulator,which generates current references directly from sensed operating points,thus supporting hardware-constrained implementation.Comprehensive numerical experiments conducted on six commercial modules from various technologies(mono,poly,and multicrystalline)demonstrate significant accuracy improvements under the IEC EN 50530 near-MPP criterion:the V-Lambert solver reduces the±10%Vmpp band error by up to 61 times compared to an explicit-model baseline.Dynamic simulations under varying irradiance,temperature,and load conditions achieve millisecond-scale settling with accurate trajectory tracking.Additionally,processor-in-the-loop experimental validation on an embedded microcontroller supports the simulation results.By unifying exact analytical modeling with embedded realization,this work advances computer modeling for PV emulation,MPPT benchmarking,and controller verification in integrated renewable energy systems.展开更多
The power output of the photovoltaic(PV) system having multiple arrays gets reduced to a great extent when it is partially shaded due to environmental hindrances. The maximum power trackers which are conventionally us...The power output of the photovoltaic(PV) system having multiple arrays gets reduced to a great extent when it is partially shaded due to environmental hindrances. The maximum power trackers which are conventionally used may not be competent enough to find the maximum power point(MPP) during partially shaded conditions. The sensible reason for the failure of conventional trackers is during partial shaded conditions the PV arrays exhibit multi peak power curves, thereby making simple maximum power point tracking(MPPT) algorithms like perturb and observe(P&O) to get stuck with local maxima instead of capturing global maxima.Therefore, global search MPPT aided by evolutionary and swarm intelligence algorithms will be conducive to find global power point during partially shaded conditions. This work suggests a unified controller which feeds control signal to its power electronic conditioner placed at each module. The evolutionary algorithm which is taken into consideration in this work is differential evolution(DE).The performance of the proposed method is compared to the classical un-dimensional search controller and it is evident from the Matlab/Simulink results that the unified controller prevails over the distributed counterpart.展开更多
The operation and power generation of utility-scale solar energy infrastructure in desert areas are affected by changes in surface erosion processes resulting from the construction of solar photovoltaic(PV)power stati...The operation and power generation of utility-scale solar energy infrastructure in desert areas are affected by changes in surface erosion processes resulting from the construction of solar photovoltaic(PV)power stations.However,few studies have addressed the interactions between solar PV arrays and aeolian erosion processes.In this study,wind flow field characteristics and the vertical distribution of sediments were investigated in the near-surface transport layer at three different locations with respect to the solar PV arrays in a 200 WM-p PV power station in the central Hobq Desert,northwestern China.The results indicate that the sediment transport varied around the panels,with the greatest transport occurring between the panels,followed by behind and in front of the panels.The sediment fluxes of all of the observation sites obey an exponential function.The secondary flow field zones formed around the PV panels:the conflux accelerating zone between the panels,the resistance decelerating zone of the under panels,and the transition zone of the rapid velocity increase in front of and behind the panels.This resulted in a greater shear force in front of the panels under the downward flow diversion effect of PV panels,and the wind erosion depressions were finally formed here.The results of this study provide information for planning better technical schemes for wind-sand hazards at solar PV power stations,which would ensure operational stability and safety in desert areas.展开更多
Deserts are ideal places to develop ground-mounted large-scale solar photovoltaic (PV) powerstation. Unfortunately, solar energy production, operation, and maintenance are affected bygeomorphological changes caused by...Deserts are ideal places to develop ground-mounted large-scale solar photovoltaic (PV) powerstation. Unfortunately, solar energy production, operation, and maintenance are affected bygeomorphological changes caused by surface erosion that may occur after the construction of the solar PVpower station. In order to avoid damage to a solar PV power station in sandy areas, it is necessary toinvestigate the characteristics of wind-sand movement under the interference of solar PV array. The studywas undertaken by measuring sediment transport of different wind directions above shifting dunes andthree observation sites around the PV panels in the Hobq Desert, China. The results showed that the twoparameterexponential function provides better fit for the measured flux density profiles to the near-surfaceof solar PV array. However, the saltation height of sand particles changes with the intersection anglebetween the solar PV array and wind direction exceed 45°. The sediment transport rate above shifting duneswas always the greatest, while that around the test PV panels varied accordingly to the wind direction.Moreover, the aeolian sediment transport on the solar PV array was significantly affected by wind direction.The value of sand inhibition rate ranged from 35.46% to 88.51% at different wind directions. When theintersection angle exceeds 45°, the mean value of sediment transport rate above the solar PV array reducesto 82.58% compared with the shifting dunes. The results of our study expand our understanding of theformation and evolution of aeolian geomorphology at the solar PV footprint. This will facilitate the designand control engineering plans for solar PV array in sandy areas that operate according to the wind regime.展开更多
This paper mainly aims at the modeling problem of the photovoltaic (PV) array with a 30 kW PV grid-connected generation system. An iterative method for the time-varying parameters is proposed to model a plant of PV ar...This paper mainly aims at the modeling problem of the photovoltaic (PV) array with a 30 kW PV grid-connected generation system. An iterative method for the time-varying parameters is proposed to model a plant of PV array. The relationship of PV cell and PV array is obtained and the solution for PV array model is unique. The PV grid-connected generation system is used to demonstrate the effectiveness of the proposed method by comparing the calculated values with the actual output of the system.展开更多
In this paper,a computer-controlled photovoltaic(PV)array simulator consisted of a synchronous buck DC converter and its associate control software is proposed and developed to simulate the current-voltage(I-V)output ...In this paper,a computer-controlled photovoltaic(PV)array simulator consisted of a synchronous buck DC converter and its associate control software is proposed and developed to simulate the current-voltage(I-V)output characteristics of a real-time PV array with actual loads connected.The main advantage of this simulator is its ability in simulating different types and sizes of arrays under various illumination and temperature conditions.It can replace the actual PV array and perform all the simulations indoor instead of outside field testing.The mathematical model implemented in this system requires minimum manufacturer's data.This system is a very cost effective and reliable laboratory tool to investigate the output characteristics of PV array under various weather conditions,and is helpful for developing new maximum power point tracking(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 United Nations’Sustainable Development Goals(SDGs)highlight the importance of affordable and clean energy sources.Solar energy is a perfect example,being both renewable and abundant.Its popularity shows no signs ...The United Nations’Sustainable Development Goals(SDGs)highlight the importance of affordable and clean energy sources.Solar energy is a perfect example,being both renewable and abundant.Its popularity shows no signs of slowing down,with solar photovoltaic(PV)panels being the primary technology for converting sunlight into electricity.Advancements are continuously being made to ensure cost-effectiveness,high-performing cells,extended lifespans,and minimal maintenance requirements.This study focuses on identifying suitable locations for implementing solar PVsystems at theUniversityMalaysia PahangAl SultanAbdullah(UMPSA),Pekan campus including buildings,water bodies,and forest areas.A combined technical and economic analysis is conducted using Helioscope for simulations and the Photovoltaic Geographic Information System(PVGIS)for economic considerations.Helioscope simulation examine case studies for PV installations in forested areas,lakes,and buildings.This approach provides comprehensive estimations of solar photovoltaic potential,annual cost savings,electricity costs,and greenhouse gas emission reductions.Based on land coverage percentages,Floatovoltaics have a large solar PV capacity of 32.3 Megawatts(MW);forest-based photovoltaics(Forestvoltaics)achieve maximum yearly savings of RM 37,268,550;and Building Applied Photovoltaics(BAPV)have the lowest CO2 emissions and net carbon dioxide reduction compared to other plant sizes.It also clarifies the purpose of using both software tools to achieve a comprehensive understanding of both technical and economic aspects.展开更多
The development of vehicle integrated photovoltaics-powered electric vehicles (VIPV-EV) significantly reduces CO<sub>2</sub> emissions from the transport sector to realize a decarbonized society. Although ...The development of vehicle integrated photovoltaics-powered electric vehicles (VIPV-EV) significantly reduces CO<sub>2</sub> emissions from the transport sector to realize a decarbonized society. Although long-distance driving of VIPV-EV without electricity charging is expected in sunny regions, driving distance of VIPV-EV is affected by climate conditions such as solar irradiation and temperature rise of PV modules. In this paper, detailed analytical results for effects of climate conditions such as solar irradiation and temperature rise of PV modules upon driving distance of the VIPV-EV were presented by using test data for Toyota Prius and Nissan Van demonstration cars installed with high-efficiency InGaP/GaAs/InGaAs 3-junction solar cell modules with a module efficiency of more than 30%. The temperature rise of some PV modules studied in this study was shown to be expressed by some coefficients related to solar irradiation, wind speed and radiative cooling. The potential of VIPV-EV to be deployed in 10 major cities was also analyzed. Although sunshine cities such as Phoenix show the high reduction ratio of driving range with 17% due to temperature rise of VIPV modules, populous cities such as Tokyo show low reduction ratio of 9%. It was also shown in this paper that the difference between the driving distance of VIPV-EV driving in the morning and the afternoon is due to PV modules’ radiative cooling. In addition, the importance of heat dissipation of PV modules and the development of high-efficiency PV modules with better temperature coefficients was suggested in order to expand driving range of VIPV-EV. The effects of air-conditioner usage and partial shading in addition to the effects of temperature rise of VIPV modules were suggested as the other power losses of VIPV-EV.展开更多
In this paper new technique is developed to monitor the health status of the PV panels in the array. For finding the health status short circuit current is measured continuously over a fixed time period. This techniqu...In this paper new technique is developed to monitor the health status of the PV panels in the array. For finding the health status short circuit current is measured continuously over a fixed time period. This technique can classify the health status into four categories such as Healthy, Low Fault, Medium Fault and High Fault. By this classification faulty operation can be rectified and power generation may be improved. In case of high faults, PV panels can be protected. The cost requirement for the implementation is very low. The proposed technique is implemented in MATLAB Simulation and hardware. The array considered in this paper is 2 × 2 Series Parallel.展开更多
基金financially supported in part by the Natural Science Foundation of Fujian,China,under Grant 2021J01633.
文摘This paper proposes a fingerprint matching method integrating transfer learning and online learning to tackle the challenges of environmental adaptability and dynamic interference resistance in photovoltaic(PV)array DC arc fault location methods based on electromagnetic radiation(EMR)signals.Initially,a comprehensive analysis of the time–frequency characteristics of series arc EMR signals is carried out to pinpoint effective data sources that reflect fault features.Subsequently,a multi-kernel domain-adversarial neural network(MKDANN)is introduced to extract domain-invariant features,and a feature extractor designed specifically for fingerprint matching is devised.To reduce inter-domain distribution differences,a multi-kernel maximum mean discrepancy(MK-MMD)is integrated into the adaptation layer.Moreover,to deal with dynamic environmental changes in real-world situations,the support-class passive aggressive(SPA)algorithm is utilized to adjust model parameters in real time.Finally,MKDANN and SPA technologies are smoothly combined to build a fully operational fault location model.Experimental results indicate that the proposed method attains an overall fault location accuracy of at least 95%,showing strong adaptability to environmental changes and robust interference resistance while maintaining excellent online learning capabilities during model migration.
文摘Conventional concentrator photovoltaics(CPV)face a persistent trade-off between high efficiency and high cost,driven by expensive multi-junction solar cells and complex active cooling systems.This study presents a computational investigation of a novel Multi-Focal Pyramidal Array(MFPA)-based CPV system designed to overcome this limitation.The MFPA architecture employs a geometrically optimized pyramidal concentrator to distribute concen-trated sunlight onto strategically placed,low-cost monocrystalline silicon cells,enabling high efficiency energy capture while passively managing thermal loads.Coupled optical thermal electrical simulations in COMSOL Multiphysics demonstrate a geometric concentration ratio of 120×,with system temperatures maintained below 110℃ under standard 1000 W/m2 Direct Normal Irradiance(DNI).Ray tracing confirms 95%optical efficiency and a concentrated light spot radius of 2.48 mm.Compared with conventional CPV designs,the MFPA improves power-per-cost by 25%and reduces tracking requirements by 50%owing to its wide±15°acceptance angle.These results highlight the MFPA’s potential as a scalable,low-cost,and energy-efficient pathway for expanding solar power generation.
基金supported by the Gansu Provincial Department of Education Industry Support Plan Project(2025CYZC-018).
文摘In order to address the challenges posed by complex background interference,high miss-detection rates of micro-scale defects,and limited model deployment efficiency in photovoltaic(PV)module defect detection,this paper proposes an efficient detection framework based on an improved YOLOv11 architecture.First,a Re-parameterized Convolution(RepConv)module is integrated into the backbone to enhance the model’s sensitivity to fine-grained defects—such as micro-cracks and hot spots—while maintaining high inference efficiency.Second,a Multi-Scale Feature Fusion Convolutional Block Attention Mechanism(MSFF-CBAM)is designed to guide the network toward critical defect regions by jointly modeling channel-wise and spatial attention.This mechanism effectively strengthens the specificity and robustness of feature representations.Third,a lightweight Dynamic Sampling Module(DySample)is employed to replace conventional upsampling operations,thereby improving the localization accuracy of small-scale defect targets.Experimental evaluations conducted on the PVEL-AD dataset demonstrate that the proposed RMDYOLOv11 model surpasses the baseline YOLOv11 in terms of mean Average Precision(mAP)@0.5,Precision,and Recall,achieving respective improvements of 4.70%,1.51%,and 5.50%.The model also exhibits notable advantages in inference speed and model compactness.Further validation on the ELPV dataset confirms the model’s generalization capability,showing respective performance gains of 1.99%,2.28%,and 1.45%across the same metrics.Overall,the enhanced model significantly improves the accuracy of micro-defect identification on PV module surfaces,effectively reducing both false negatives and false positives.This advancement provides a robust and reliable technical foundation for automated PV module defect detection.
基金funded by the Malaysian Ministry of Higher Education through the Fundamental Research Grant Scheme(FRGS/1/2024/ICT02/UCSI/02/1).
文摘Accurate estimation of photovoltaic(PV)parameters is essential for optimizing solar module perfor-mance and enhancing resource efficiency in renewable energy systems.This study presents a process innovation by introducing,for the first time,the Triangulation Topology Aggregation Optimizer(TTAO)integrated with parallel computing to address PV parameter estimation challenges.The effectiveness and robustness of TTAO are rigorously evaluated using two standard benchmark datasets(KC200GT and R.T.C.France solar cells)and a real-world dataset(Poly70W solar module)under single-,double-,and triple-diode configurations.Results show that TTAO consistently achieves superior accuracy by producing the lowest RMSE values and faster convergence compared to state-of-the-art metaheuristic algorithms.In addition,the integration of parallel computing significantly enhances computational efficiency,reducing execution time by up to 85%without compromising accuracy.Validation using real-world data further demonstrates TTAO’s adaptability and practical relevance in renewable energy systems,effectively bridging the gap between theoretical modeling and real-world implementation for PV system monitoring and optimization,contributing to climate mitigation through improved solar energy performance.
基金funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R442)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Accurate parameter extraction of photovoltaic(PV)models plays a critical role in enabling precise performance prediction,optimal system sizing,and effective operational control under diverse environmental conditions.While a wide range of metaheuristic optimisation techniques have been applied to this problem,many existing methods are hindered by slow convergence rates,susceptibility to premature stagnation,and reduced accuracy when applied to complex multi-diode PV configurations.These limitations can lead to suboptimal modelling,reducing the efficiency of PV system design and operation.In this work,we propose an enhanced hybrid optimisation approach,the modified Spider Wasp Optimization(mSWO)with Opposition-Based Learning algorithm,which integrates the exploration and exploitation capabilities of the Spider Wasp Optimization(SWO)metaheuristic with the diversityenhancing mechanism of Opposition-Based Learning(OBL).The hybridisation is designed to dynamically expand the search space coverage,avoid premature convergence,and improve both convergence speed and precision in highdimensional optimisation tasks.The mSWO algorithm is applied to three well-established PV configurations:the single diode model(SDM),the double diode model(DDM),and the triple diode model(TDM).Real experimental current-voltage(I-V)datasets from a commercial PV module under standard test conditions(STC)are used for evaluation.Comparative analysis is conducted against eighteen advanced metaheuristic algorithms,including BSDE,RLGBO,GWOCS,MFO,EO,TSA,and SCA.Performance metrics include minimum,mean,and maximum root mean square error(RMSE),standard deviation(SD),and convergence behaviour over 30 independent runs.The results reveal that mSWO consistently delivers superior accuracy and robustness across all PV models,achieving the lowest RMSE values of 0.000986022(SDM),0.000982884(DDM),and 0.000982529(TDM),with minimal SD values,indicating remarkable repeatability.Convergence analyses further show that mSWO reaches optimal solutions more rapidly and with fewer oscillations than all competing methods,with the performance gap widening as model complexity increases.These findings demonstrate that mSWO provides a scalable,computationally efficient,and highly reliable framework for PV parameter extraction.Its adaptability to models of growing complexity suggests strong potential for broader applications in renewable energy systems,including performance monitoring,fault detection,and intelligent control,thereby contributing to the optimisation of next-generation solar energy solutions.
基金funded by Scientific Research Deanship at University of Ha’il-Saudi Arabia through project number(RG-24014).
文摘We present a computer-modeling framework for photovoltaic(PV)source emulation that preserves the exact single-diode physics while enabling iteration-free,real-time evaluation.We derive two closed-form explicit solvers based on the Lambert W function:a voltage-driven V-Lambert solver for high-fidelity I–V computation and a resistance-driven R-Lambert solver designed for seamless integration in a closed-loop PV emulator.Unlike Taylor-linearized explicit models,our proposed formulation retains the exponential nonlinearity of the PV equations.It employs a numerically stable analytical evaluation that eliminates the need for lookup tables and root-finding,all while maintaining limited computational costs and a small memory footprint.The R-Lambert model is integrated into a buck-converter emulator equipped with a discrete PI regulator,which generates current references directly from sensed operating points,thus supporting hardware-constrained implementation.Comprehensive numerical experiments conducted on six commercial modules from various technologies(mono,poly,and multicrystalline)demonstrate significant accuracy improvements under the IEC EN 50530 near-MPP criterion:the V-Lambert solver reduces the±10%Vmpp band error by up to 61 times compared to an explicit-model baseline.Dynamic simulations under varying irradiance,temperature,and load conditions achieve millisecond-scale settling with accurate trajectory tracking.Additionally,processor-in-the-loop experimental validation on an embedded microcontroller supports the simulation results.By unifying exact analytical modeling with embedded realization,this work advances computer modeling for PV emulation,MPPT benchmarking,and controller verification in integrated renewable energy systems.
文摘The power output of the photovoltaic(PV) system having multiple arrays gets reduced to a great extent when it is partially shaded due to environmental hindrances. The maximum power trackers which are conventionally used may not be competent enough to find the maximum power point(MPP) during partially shaded conditions. The sensible reason for the failure of conventional trackers is during partial shaded conditions the PV arrays exhibit multi peak power curves, thereby making simple maximum power point tracking(MPPT) algorithms like perturb and observe(P&O) to get stuck with local maxima instead of capturing global maxima.Therefore, global search MPPT aided by evolutionary and swarm intelligence algorithms will be conducive to find global power point during partially shaded conditions. This work suggests a unified controller which feeds control signal to its power electronic conditioner placed at each module. The evolutionary algorithm which is taken into consideration in this work is differential evolution(DE).The performance of the proposed method is compared to the classical un-dimensional search controller and it is evident from the Matlab/Simulink results that the unified controller prevails over the distributed counterpart.
基金supported by the Major Science and Technology Projects of Inner Mongolia Autonomous Region of China(zdzx2018058-3)the National Key Research and Development Project of China(2016YFC0500906-3)the Scientific and Technological Innovation Guiding Fund Project of Inner Mongolia Autonomous Region of China and the Scientific Research Project of Universities in Inner Mongolia Autonomous Region of China(NJZY19052)。
文摘The operation and power generation of utility-scale solar energy infrastructure in desert areas are affected by changes in surface erosion processes resulting from the construction of solar photovoltaic(PV)power stations.However,few studies have addressed the interactions between solar PV arrays and aeolian erosion processes.In this study,wind flow field characteristics and the vertical distribution of sediments were investigated in the near-surface transport layer at three different locations with respect to the solar PV arrays in a 200 WM-p PV power station in the central Hobq Desert,northwestern China.The results indicate that the sediment transport varied around the panels,with the greatest transport occurring between the panels,followed by behind and in front of the panels.The sediment fluxes of all of the observation sites obey an exponential function.The secondary flow field zones formed around the PV panels:the conflux accelerating zone between the panels,the resistance decelerating zone of the under panels,and the transition zone of the rapid velocity increase in front of and behind the panels.This resulted in a greater shear force in front of the panels under the downward flow diversion effect of PV panels,and the wind erosion depressions were finally formed here.The results of this study provide information for planning better technical schemes for wind-sand hazards at solar PV power stations,which would ensure operational stability and safety in desert areas.
基金This research was supported by the Major Science and Technology Projects of Inner Mongolia Autonomous Region of China(zdzx2018058-3)the National Key Research and Development Project of China(2016YFC0500906-3)the Scientific and Technological Innovation Guiding Fund Project of Inner Mongolia Autonomous Region of China(R&D and Demonstration of Ecological Deserticulture Technology of Solar Photovoltaic Power Station in Sand Area)and the Scientific Research Project of Universities in Inner Mongolia Autonomous Region of China(NJZY19052).
文摘Deserts are ideal places to develop ground-mounted large-scale solar photovoltaic (PV) powerstation. Unfortunately, solar energy production, operation, and maintenance are affected bygeomorphological changes caused by surface erosion that may occur after the construction of the solar PVpower station. In order to avoid damage to a solar PV power station in sandy areas, it is necessary toinvestigate the characteristics of wind-sand movement under the interference of solar PV array. The studywas undertaken by measuring sediment transport of different wind directions above shifting dunes andthree observation sites around the PV panels in the Hobq Desert, China. The results showed that the twoparameterexponential function provides better fit for the measured flux density profiles to the near-surfaceof solar PV array. However, the saltation height of sand particles changes with the intersection anglebetween the solar PV array and wind direction exceed 45°. The sediment transport rate above shifting duneswas always the greatest, while that around the test PV panels varied accordingly to the wind direction.Moreover, the aeolian sediment transport on the solar PV array was significantly affected by wind direction.The value of sand inhibition rate ranged from 35.46% to 88.51% at different wind directions. When theintersection angle exceeds 45°, the mean value of sediment transport rate above the solar PV array reducesto 82.58% compared with the shifting dunes. The results of our study expand our understanding of theformation and evolution of aeolian geomorphology at the solar PV footprint. This will facilitate the designand control engineering plans for solar PV array in sandy areas that operate according to the wind regime.
基金Supported by the National Natural Science Foundation of China (61233004, 61074061)the State Key Development Program for Basic Research of China (2013CB035500)+1 种基金the National High Technology Research and Development Program of China(2011AA040901)Key Project of Ministry of Railways of China (J2011J004)
文摘This paper mainly aims at the modeling problem of the photovoltaic (PV) array with a 30 kW PV grid-connected generation system. An iterative method for the time-varying parameters is proposed to model a plant of PV array. The relationship of PV cell and PV array is obtained and the solution for PV array model is unique. The PV grid-connected generation system is used to demonstrate the effectiveness of the proposed method by comparing the calculated values with the actual output of the system.
文摘In this paper,a computer-controlled photovoltaic(PV)array simulator consisted of a synchronous buck DC converter and its associate control software is proposed and developed to simulate the current-voltage(I-V)output characteristics of a real-time PV array with actual loads connected.The main advantage of this simulator is its ability in simulating different types and sizes of arrays under various illumination and temperature conditions.It can replace the actual PV array and perform all the simulations indoor instead of outside field testing.The mathematical model implemented in this system requires minimum manufacturer's data.This system is a very cost effective and reliable laboratory tool to investigate the output characteristics of PV array under various weather conditions,and is helpful for developing new maximum power point tracking(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.
基金the financial support provided by Universiti Malaysia Pahang Al Sultan Abdullah(www.umpsa.edu.my,accessed 10 April 2024)through the Doctoral Research Scheme(DRS)toMr.Rittick Maity and the Postgraduate Research Scheme(PGRS220390).
文摘The United Nations’Sustainable Development Goals(SDGs)highlight the importance of affordable and clean energy sources.Solar energy is a perfect example,being both renewable and abundant.Its popularity shows no signs of slowing down,with solar photovoltaic(PV)panels being the primary technology for converting sunlight into electricity.Advancements are continuously being made to ensure cost-effectiveness,high-performing cells,extended lifespans,and minimal maintenance requirements.This study focuses on identifying suitable locations for implementing solar PVsystems at theUniversityMalaysia PahangAl SultanAbdullah(UMPSA),Pekan campus including buildings,water bodies,and forest areas.A combined technical and economic analysis is conducted using Helioscope for simulations and the Photovoltaic Geographic Information System(PVGIS)for economic considerations.Helioscope simulation examine case studies for PV installations in forested areas,lakes,and buildings.This approach provides comprehensive estimations of solar photovoltaic potential,annual cost savings,electricity costs,and greenhouse gas emission reductions.Based on land coverage percentages,Floatovoltaics have a large solar PV capacity of 32.3 Megawatts(MW);forest-based photovoltaics(Forestvoltaics)achieve maximum yearly savings of RM 37,268,550;and Building Applied Photovoltaics(BAPV)have the lowest CO2 emissions and net carbon dioxide reduction compared to other plant sizes.It also clarifies the purpose of using both software tools to achieve a comprehensive understanding of both technical and economic aspects.
文摘The development of vehicle integrated photovoltaics-powered electric vehicles (VIPV-EV) significantly reduces CO<sub>2</sub> emissions from the transport sector to realize a decarbonized society. Although long-distance driving of VIPV-EV without electricity charging is expected in sunny regions, driving distance of VIPV-EV is affected by climate conditions such as solar irradiation and temperature rise of PV modules. In this paper, detailed analytical results for effects of climate conditions such as solar irradiation and temperature rise of PV modules upon driving distance of the VIPV-EV were presented by using test data for Toyota Prius and Nissan Van demonstration cars installed with high-efficiency InGaP/GaAs/InGaAs 3-junction solar cell modules with a module efficiency of more than 30%. The temperature rise of some PV modules studied in this study was shown to be expressed by some coefficients related to solar irradiation, wind speed and radiative cooling. The potential of VIPV-EV to be deployed in 10 major cities was also analyzed. Although sunshine cities such as Phoenix show the high reduction ratio of driving range with 17% due to temperature rise of VIPV modules, populous cities such as Tokyo show low reduction ratio of 9%. It was also shown in this paper that the difference between the driving distance of VIPV-EV driving in the morning and the afternoon is due to PV modules’ radiative cooling. In addition, the importance of heat dissipation of PV modules and the development of high-efficiency PV modules with better temperature coefficients was suggested in order to expand driving range of VIPV-EV. The effects of air-conditioner usage and partial shading in addition to the effects of temperature rise of VIPV modules were suggested as the other power losses of VIPV-EV.
文摘In this paper new technique is developed to monitor the health status of the PV panels in the array. For finding the health status short circuit current is measured continuously over a fixed time period. This technique can classify the health status into four categories such as Healthy, Low Fault, Medium Fault and High Fault. By this classification faulty operation can be rectified and power generation may be improved. In case of high faults, PV panels can be protected. The cost requirement for the implementation is very low. The proposed technique is implemented in MATLAB Simulation and hardware. The array considered in this paper is 2 × 2 Series Parallel.
