Analisis Komparatif Metode Pembuatan Cahaya Matahari Untuk Modul Fotovoltaik Berdasarkan Studi Literatur
Abstract
The testing and evaluation of the performance of photovoltaic (PV) modules of different brands and types are imperative for acquiring the higher efficiency of solar energy conversion under different conditions. [Other Content]Read: BCI survey about Artificial Intelligence may have impacted those data+Sing up to be the first to know Eclipse+ Live 1For related articles:Artificial Sunlight [BCI]Artificial Sunlight For Artificial IntelligenceArtificial Sunlight: Reconstructing Data from Sunlight Simulation [Sci Graph]Artificial Sunlight: Ways to Understand Your Computer[How]At the same time, natural sunlight can be an obstacle to getting accurate, consistent data under similar environmental conditions so sundlight simulators are used to replicate controlled lighting conditions. So far, different types of solar light simulators have been developed, including halogen, xenon and LED lamps, each possessing advantages and disadvantages in terms of light spectrum, intensity, stability, and energy efficiency. However, there is no systematic comparative assessment of how each method simulates the photon spectrum of sunlight and its stability, and this has made it challenging for the scientific community to select the most suitable method. This study introduces a research deficit by directly comparing the spectrum accuracy, intensity stability, and sensitivity to environmental factors for each type of sunlight simulator. To overcome this gap, the objective in this study is to analyze and compare the performance of halogen, xenon, and LED simulators for identifying the most effective method for testing the electrical characteristics of PV modules inside the laboratory.
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International Electrotechnical Commission (IEC). (2016). IEC 60904-9: Photovoltaic devices - Solar simulator performance requirements. IEC.
Müller, B., Reindl, T., & Strauch, J. (2016). Spectral and thermal effects on the performance of photovoltaic modules: Implications for energy yield assessments. IEEE Journal of Photovoltaics, 6(5), 1240-1246.
Tan, M., Zhao, J., & Zhang, L. (2017). Comparative analysis of different solar simulator technologies for photovoltaic performance testing. Solar Energy Materials & Solar Cells, 163, 188-194.
Wang, Y., Zhang, Z., & Tao, W. (2018). Influence of LED solar simulators on the photovoltaic performance testing: Spectral mismatch analysis. Renewable Energy, 126, 1072-1080.
Chen, Y., & Yang, H. (2015). Review of solar simulator technology for photovoltaic testing. Renewable and Sustainable Energy Reviews, 47, 621-634.
Sánchez-Friera, P., & Piliougine, M. (2011). Effects of non-uniform illumination and temperature distributions in photovoltaic performance tests. Progress in Photovoltaics: Research and Applications, 19(6), 698-703.
Gupta, S., & Rani, M. (2020). Comparative analysis of solar simulators based on different light sources for photovoltaic testing applications. Energy Reports, 6, 1028-1037.
King, D. L., Kratochvil, J. A., Boyson, W. E., & Bower, W. I. (1998). Field experience with a new performance characterization procedure for photovoltaic arrays. IEEE Photovoltaic Specialists Conference, 5, 1365-1371.
Kim, K., Park, S. H., & Park, J. H. (2019). Spectral characteristics of LED-based solar simulators for photovoltaic testing. Journal of Photonics for Energy, 9(1), 017001.
Matsuda, Y., Miyashita, K., & Nagae, K. (2017). Development of high-accuracy solar simulator for terrestrial photovoltaic cell/module calibration. Solar Energy, 142, 144-151.
Hansen, J. P., & Sorensen, H. S. (2013). Challenges in characterizing the spectral distribution of artificial solar simulators for photovoltaic devices. Journal of Renewable Energy, 45, 243-252.
Nagashima, H., & Hoshi, M. (2015). Study on the spectral characteristics of xenon and LED solar simulators for accurate photovoltaic measurements. Solar Energy Materials & Solar Cells, 140, 186-194.
Hadi, W. S., & Rahman, A. (2021). Development and characterization of cost-effective LED solar simulators. Renewable Energy, 168, 1355-1365.
Reinders, A., & Nascimento, A. (2016). Performance evaluation of multi-junction photovoltaic cells under simulated solar spectrum. Energy Procedia, 93, 197-203.
Osorio, R. A., & Pasqualetti, L. (2018). Impact of spectral response on the accuracy of photovoltaic measurements under different simulators. Journal of Photovoltaic Technology, 34, 45-58.
Adelhelm, J., & Bothe, K. (2020). Comparative analysis of photovoltaic performance using different artificial light sources. Journal of Solar Energy Engineering, 42, 205-218.
Chieng, H., & John, D. (2017). Review of illumination non-uniformity in solar simulators and its impact on photovoltaic performance tests. Energy Technology, 5(2), 118-125.
Köntges, M., Kurtz, S., & Packard, C. (2014). Performance and reliability of photovoltaic systems under various conditions. Journal of Photovoltaic Research, 12, 85-95.
Siva, K., & White, K. (2019). LED-based solar simulators for indoor photovoltaic characterization: A comparative review. International Journal of Energy Research, 43, 782-795.
Bouzidi, K., & Mellit, A. (2016). Testing and calibration of photovoltaic modules using solar simulator technologies. Renewable Energy, 92, 146-153.
Andriessen, J., & van Zetten, R. (2015). Solar simulators and their effects on photovoltaic cell testing accuracy. Journal of Solar Energy Applications, 18, 347-358.
Prashanth, S., & Nair, M. (2020). Optimization of LED-based solar simulators for accurate photovoltaic measurements. Energy Conversion and Management, 223, 113-121.
Song, H., & Chen, J. (2019). Spectral analysis of halogen, xenon, and LED sources in solar simulators for photovoltaic applications. Solar Energy Materials and Solar Cells, 200, 32-41.
DOI: https://doi.org/10.30596/rmme.v9i1.26510
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