PV Array Reconfiguration Based on Genetic Algorithm for Maximum Power Extraction and Energy Impact Analysis

Durango-Flórez, Mariana; Montoya, Daniel; Trejos-Grisales, Luz Adriana; Ramos‐Paja, Carlos Andrés

doi:10.3390/su14073764

Cited by 11 publications

(5 citation statements)

References 38 publications

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“…The practicality of the switching matrix was not mentioned Mariana, et al [18] 2022 Genetic Algorithm Simulation Power Execution time was mentioned clearly along with PV size…”

Section: Simulation and Experimentsmentioning

confidence: 99%

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Photovoltaic Array Reconfiguration under Partial Shading Conditions Based on Short-Circuit Current Estimated by Convolutional Neural Network

et al. 2022

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Partial shading conditions (PSC) have negative effects on the operation of photovoltaic (PV) systems. In this paper, a PV array reconfiguration method is developed to minimize power losses of PV arrays under partial shading conditions. The proposed reconfiguration method is based on equalizing the reduction of the short-circuit current of the PV modules in the PV array. Eight state-of-the-art Convolutional Neural Network models are employed to estimate the effect of shading on the short-circuit current of a PV module. These models include LeNet-5, AlexNet, VGG 11, VGG 19, Inception V3, ResNet 18, ResNet 34, and ResNet 50. Among eight models, the VGG 19 achieves the best accuracy on 1842 sample images. Therefore, this model is used to estimate the ratio of the actual short-circuit current and the estimated short-circuit current in four studied shading scenarios. This ratio decides the switching rule between PV modules throughout the PV array under PSC. A 2×2 experimental PV array shows that the proposed reconfiguration method improves the output power from 5.81% to 25.19% in four shading patterns. Accordingly, the power losses are reduced from 1.32% to 13.75%. The power improvement and the reduction of power losses of the proposed dynamic PV array reconfiguration system under four case studies demonstrates its effectiveness in addressing the effects of PSC on the PV array.

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“…The practicality of the switching matrix was not mentioned Mariana, et al [18] 2022 Genetic Algorithm Simulation Power Execution time was mentioned clearly along with PV size…”

Section: Simulation and Experimentsmentioning

confidence: 99%

“…Ref. [18] uses the Genetic algorithm to determine the optimal configuration of the PV array under PSC. The execution time is mentioned clearly along with the PV size.…”

Section: Introductionmentioning

confidence: 99%

Photovoltaic Array Reconfiguration under Partial Shading Conditions Based on Short-Circuit Current Estimated by Convolutional Neural Network

et al. 2022

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“…By carefully designing the Sudoku reconfiguration strategy, it is possible to significantly reduce the negative impact of partial-shading on the power output of the PV system. In the dynamic reconfiguration technique [22,23], the electrical connections of PV modules are changed dynamically with the help of sensors, switches, and control algorithms based on the irradiance of the PV modules. In [24], to supply the maximum power to the motor, a control algorithm for electrical array reconfiguration has been implemented using fuzzy logic controller.…”

Section: Introductionmentioning

confidence: 99%

Improved-Odd-Even-Prime Reconfiguration to Enhance the Output Power of Rectangular Photovoltaic Array under Partial Shading Conditions

2023

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The output power of a PV (photovoltaic) array decreases due to the partial shading condition (PSC). If one or more PV modules receives less irradiance compared to other PV modules in a PV array then it is called PSC. To enhance the output power of PV array under PSC, Sudoku, and Optimal Sudoku Reconfiguration techniques are available in the literature for perfect squared PV arrays, such as 4×4, 9×9, and 16×16. Odd–Even and Odd–Even–Prime reconfigurations are available for rectangular PV arrays. To enhance the output power of rectangular PV array further, this paper proposed a new reconfiguration technique called Improved Odd–Even–Prime reconfiguration. To validate the proposed method, two PV arrays 9×9 and 8×9 have been implemented.

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“…Doyle et al [19] carried out aerodynamic optimization for freight trucks using a genetic algorithm with computational fluid dynamics. Florez et al [20] proposed a method based on a genetic algorithm for reconfiguration and energy impact analysis of different PV arrays under different environmental conditions. Meerimatha et al [21] investigated the effect of partial shading on the power output by reconfiguring PV arrays using a Genetic algorithm.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Photovoltaic Panel Array Configurations to Reduce Lift Force Using Genetic Algorithm and CFD

et al. 2022

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Aerodynamic lift force acting on the solar structure is important while designing the counterweight for rooftop-mounted solar systems. Due to their unique configuration, the load estimated for solar structures using international building codes can be either higher or lower than the actual. Computational Fluid Dynamics(CFD) simulations haveproven to be an efficient tool for estimating wind loads on solar panels for design purposes and identifying critical design cases.Computational Fluid Dynamics (CFD) simulations usually require high computation power, and slight changes in geometry to find optimum configuration can be time-consuming. An optimization method to minimize lift force effects on solar photovoltaic (PV) arrays installed on rooftops usesthe Computational Fluid Dynamics (CFD)and genetic algorithms proposed in this paper. The tilt angle and pitch between two rows of solar panels were parameterized, and a genetic algorithm was used to search for aconfiguration resulting in minimum wind lift force acting on the solar photovoltaic plant. Only combinations with a performance ratio > 80% were considered. Three different rooftopphotovoltaic (PV) plant layout configurations wereanalyzed in this research. Two rows of photovoltaic (PV) panel arrays wereconsidered for optimization in the 2D domain using ANSYS Fluent. Results showed that the difference in wind-liftforce between optimized configurations against that with maximum lift force configuration for all three cases above was fifty percent.

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PV Array Reconfiguration Based on Genetic Algorithm for Maximum Power Extraction and Energy Impact Analysis

Cited by 11 publications

References 38 publications

Photovoltaic Array Reconfiguration under Partial Shading Conditions Based on Short-Circuit Current Estimated by Convolutional Neural Network

Photovoltaic Array Reconfiguration under Partial Shading Conditions Based on Short-Circuit Current Estimated by Convolutional Neural Network

Improved-Odd-Even-Prime Reconfiguration to Enhance the Output Power of Rectangular Photovoltaic Array under Partial Shading Conditions

Optimization of Photovoltaic Panel Array Configurations to Reduce Lift Force Using Genetic Algorithm and CFD

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