Solar Irradiation Fundamentals and Solar Simulators

Esen, Vedat; Sağlam, Şafak; Oral, Bülent

doi:10.1007/978-3-030-43473-1_1

Cited by 3 publications

(1 citation statement)

References 52 publications

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“…The main conclusion is that the XAI model helps understand the current advantages of PV with its use. The research paper developed by Esen et al [76] analysed the influence of timestamps, forecast horizons, input correlation analysis, data pre-and post-processing, meteorological classification, grid optimisation, uncertainty quantification and performance evaluations in PV production analysis. The study focused on the introduction of solar and radiation simulators for PV research.…”

Section: Summary Review-based Analysismentioning

confidence: 99%

Artificial Intelligence Techniques for the Photovoltaic System: A Systematic Review and Analysis for Evaluation and Benchmarking

Kumar,

Dubey,

Segovia Ramírez

et al. 2024

Arch Computat Methods Eng

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Novel algorithms and techniques are being developed for design, forecasting and maintenance in photovoltaic due to high computational costs and volume of data. Machine Learning, artificial intelligence techniques and algorithms provide automated, intelligent and history-based solutions for complex scenarios. This paper aims to identify through a systematic review and analysis the role of artificial intelligence algorithms in photovoltaic systems analysis and control. The main novelty of this work is the exploration of methodological insights in three different ways. The first approach is to investigate the applicability of artificial intelligence techniques in photovoltaic systems. The second approach is the computational study and analysis of data operations, failure predictors, maintenance assessment, safety response, photovoltaic installation issues, intelligent monitoring etc. All these factors are discussed along with the results after applying the artificial intelligence techniques on photovoltaic systems, exploring the challenges and limitations considering a wide variety of latest related manuscripts.

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Section: Summary Review-based Analysismentioning

confidence: 99%

Artificial Intelligence Techniques for the Photovoltaic System: A Systematic Review and Analysis for Evaluation and Benchmarking

Kumar,

Dubey,

Segovia Ramírez

et al. 2024

Arch Computat Methods Eng

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Toward Class AAA LED Large Scale Solar Simulator With Active Cooling System for PV Module Tests

Esen

Sağlam

Oral

et al. 2022

IEEE J. Photovoltaics

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Cost-effective and Smart AAA-Class RGB-LED-based Sun Simulator for Real-Time Characterization of Solar Cells

Nayeri

Rostami

Moghadam

2022

Preprint

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To characterize the solar cell parameters, the light emitting diode (LED)-based sun simulators have been developed using different types of LEDs and geometrical configurations in the various wavelength range. However, the optimal spectral match, spatial homogeneity, and temporal stability have not been attained in these systems. Moreover, their design is very complex, heavy, expensive, energy and time-consuming, and needs a professional operator. Here, we have introduced a cost-effective and smart RGB LED-based sun simulator that is controlled by an ARM microprocessor, which is adjustable using user-friendly windows software. The LED panel cover 22 peak wavelength in the range of 245–940 nm at 0.2 sun intensity compared with AM1.5G global solar spectrum sunlight containing 4 UV LED (245 nm), 56 RGB LED with a 10 mm center-to-center distance from each other (14 different peaks with 22nm intervals in the range of 380-680nm), five IR LEDs with different wavelengths, including 730, 740, 810, 850, and 940 nm in the area of 10×15 cm2. According to the IEC60904-9 and ASTM standards, we achieved the AAA-class performance in all three categories including spectral match, spatial homogeneity, and temporal instability for test planes 4×4 cm2 and 8 ×8 cm2 at a distance of 4 cm from the LED panel. We successfully measured the I-V parameter of the standard solar cell 3×3 cm in the real-time condition. This system is ultra-low cost, simple, user-friendly, and can be built and used in any research lab characterizing and monitoring solar cell parameters in real-time conditions.

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Solar Irradiation Fundamentals and Solar Simulators

Cited by 3 publications

References 52 publications

Artificial Intelligence Techniques for the Photovoltaic System: A Systematic Review and Analysis for Evaluation and Benchmarking

Artificial Intelligence Techniques for the Photovoltaic System: A Systematic Review and Analysis for Evaluation and Benchmarking

Toward Class AAA LED Large Scale Solar Simulator With Active Cooling System for PV Module Tests

Cost-effective and Smart AAA-Class RGB-LED-based Sun Simulator for Real-Time Characterization of Solar Cells

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