Parametric study of design factors on the performance of flexible solar modules

References

• Aberle, A. G. 2009. Thin-film solar cells. Thin Solid Films 517 (17):4706–10. doi:10.1016/j.tsf.2009.03.056.
   Web of Science ®Google Scholar
• Al-Habahbeh, O. M., R. A. Alomosh, and D. K. Aldebie. 2016. Reliability simulation of solar concentrator receiver. International Journal of Sustainable Energy 35 (8):793–801. doi:10.1080/14786451.2014.950963.
   Web of Science ®Google Scholar
• Belsky, A. A., D. Y. Glukhanich, M. J. Carrizosa, and V. V. Starshaia. 2022. Analysis of specifications of solar photovoltaic panels. Renewable and Sustainable Energy Reviews. 159:112239. November 2021. doi:10.1016/j.rser.2022.112239.
   Web of Science ®Google Scholar
• Berny, S., N. Blouin, A. Distler, H. J. Egelhaaf, M. Krompiec, A. Lohr, O. R. Lozman. 2015. Solar trees: First large-scale demonstration of fully solution coated, semitransparent, flexible organic photovoltaic modules. Advanced Science. 3(5):1500342–47. doi:10.1002/advs.201500342.
   Web of Science ®Google Scholar
• Capossio, J. P., M. P. Fabani, A. Reyes-Urrutia, R. Torres-Sciancalepore, Y. Deng, J. Baeyens, R. Rodriguez, and G. Mazza. 2022. Sustainable solar drying of brewer’s spent grains: A comparison with conventional electric convective drying. Processes. 10(2): doi:10.3390/pr10020339.
   Web of Science ®Google Scholar
• Dibb, G. 2016. Developing the next generation of flexible solar panels. Renewable Energy Focus 17 (4):140–41. doi:10.1016/j.ref.2016.07.007.
   Google Scholar
• Dong, P., M. T. F. Rodrigues, J. Zhang, R. S. Borges, K. Kalaga, A. L. M. Reddy, G. G. Silva, P. M. Ajayan, and J. Lou. 2017. A flexible solar cell/supercapacitor integrated energy device. Nano Energy 42:181–86. doi:10.1016/j.nanoen.2017.10.035.
   Web of Science ®Google Scholar
• Fabani, M. P., J. Pablo Capossio, M. Celia Román, W. Zhu, R. Rodriguez, and G. Mazza. 2021. Producing non-traditional flour from watermelon rind pomace: artificial neural network (ann) modeling of the drying process. Journal of Environmental Management 281 (March). doi:10.1016/j.jenvman.2020.111915.
   PubMedGoogle Scholar
• Get, R., S. M. Islam, S. Singh, and P. Mahala. 2020. Organic polymer bilayer structures for applications in flexible solar cell devices. Microelectronic Engineering 222:111200. doi:10.1016/j.mee.2019.111200.
   Web of Science ®Google Scholar
• Guarracino, I., J. Freeman, A. Ramos, S. A. Kalogirou, N. J. Ekins-Daukes, and C. N. Markides. 2019. Systematic testing of hybrid PV-Thermal (PVT) solar collectors in steady-state and dynamic outdoor conditions. Applied Energy. 240:1014–30. December 2018. doi:10.1016/j.apenergy.2018.12.049.
   Web of Science ®Google Scholar
• Hamasha, M. M., T. P. Dhakal, P. Vasekar, K. Alzoubi, S. Lu, D. Vanhart, and C. R. Westgate. 2013. Reliability of sputter deposited aluminum-doped zinc oxide under harsh environmental conditions. Solar Energy. 89. doi:10.1016/j.solener.2012.12.006.
   Web of Science ®Google Scholar
• Hashmi, G., M. S. Hasan, M. M. H. Efat, and M. H. Rahman. 2020. Portable solar panel efficiency measurement system. SN Applied Sciences 2 (1):1–7. doi:10.1007/s42452-019-1851-z.
   Web of Science ®Google Scholar
• Hu, G., W. Guo, R. Yu, X. Yang, R. Zhou, C. Pan, and Z. L. Wang. 2016. Enhanced performances of flexible zno/perovskite solar cells by piezo-phototronic effect. Nano Energy 23:27–33. doi:10.1016/j.nanoen.2016.02.057.
   Web of Science ®Google Scholar
• Karamirad, M., M. Omid, R. Alimardani, H. Mousazadeh, and S. N. Heidari. 2013. ANN based simulation and experimental verification of analytical four- and five-parameters models of pv modules. Simulation Modelling Practice and Theory 34:86–98. doi:10.1016/j.simpat.2013.02.001.
   Web of Science ®Google Scholar
• Kazem, H. A., M. T. Chaichan, A. H. A. Al-Waeli, and K. Sopian. 2022. Effect of dust and cleaning methods on mono and polycrystalline solar photovoltaic performance: an indoor experimental study. Solar Energy. 236:626–43. doi: 10.1016/j.solener.2022.03.009.
   Web of Science ®Google Scholar
• Kumar, A. 2017. Predicting efficiency of solar cells based on transparent conducting electrodes. Journal of Applied Physics 121 (1):14502. doi:10.1063/1.4973117.
   Web of Science ®Google Scholar
• Kuriakose, A. M., D. P. Kariyalil, M. Augusthy, S. Sarath, J. Jacob, and N. R. Antony. 2020. “Comparison of artificial neural network, Linear Regression and Support Vector Machine for Prediction of Solar PV Power.” 2020 IEEE Pune Section International Conference, PuneCon 2020, 53–58. 10.1109/PuneCon50868.2020.9362442.
   Google Scholar
• Lim, M. S. W., D. He, J. S. M. Tiong, S. Hanson, T. C. K. Yang, T. J. Tiong, G. T. Pan, and S. Chong. 2022. Experimental, economic and life cycle assessments of recycling end-of-life monocrystalline silicon photovoltaic modules. Journal of Cleaner Production. 340:130796. September 2021. doi:10.1016/j.jclepro.2022.130796.
   Web of Science ®Google Scholar
• Lin, Q., H. Huang, Y. Jing, H. Fu, P. Chang, D. Li, Y. Yao, and Z. Fan. 2014. Flexible photovoltaic technologies. Journal of Materials Chemistry C 2 (7):1233–47. doi:10.1039/c3tc32197e.
   Web of Science ®Google Scholar
• Liu, H., Z. Ren, Z. Liu, A. G. Aberle, T. Buonassisi, and I. M. Peters. 2017. Predicting the outdoor performance of flat-plate iii–v/si tandem solar cells. solar energy 149:77–84. doi:10.1016/j.solener.2017.04.003.
   Web of Science ®Google Scholar
• Luque, A., and S. Hegedus. 2011. Handbook of photovoltaic science and engineering. John Wiley & Sons. doi:10.1002/9780470974704.
   Google Scholar
• Madani, T., M. Boukraa, M. Aissani, T. Chekifi, A. Ziadi, and M. Zirari. 2023. Experimental investigation and numerical analysis using Taguchi and ANOVA methods for underwater friction stir welding of aluminium alloy 2017 process improvement. International Journal of Pressure Vessels and Piping. 201 . doi:10.1016/j.ijpvp.2022.104879.
   Web of Science ®Google Scholar
• Mehmood, H., T. Tauqeer, and S. Hussain. 2018. Recent progress in silicon-based solid-state solar cells. International Journal of Electronics 105 (9):1568–82. doi:10.1080/00207217.2018.1477191.
   Web of Science ®Google Scholar
• Obeidat, M. S., B. R. Melhim, and T. Qasim. 2022. The effect of changing the shape factor on the efficiency of the flexible solar modules. Renewable Energy Focus 41:118–32. doi:10.1016/j.ref.2022.02.009.
   Google Scholar
• Pazikadin, A. R., D. Rifai, K. Ali, M. Z. Malik, A. N. Abdalla, and M. A. Faraj. 2020. Solar irradiance measurement instrumentation and power solar generation forecasting based on Artificial Neural Networks (ANN): A review of five years research trend. Science of the Total Environment 715:136848. doi:10.1016/j.scitotenv.2020.136848.
   PubMed Web of Science ®Google Scholar
• Pera, D. M., I. Costa, F. Serra, G. Gaspar, K. Lobato, J. M. Serra, and J. A. Silva. 2023. Development of a metal-assisted chemical etching method to improve light-capture in monocrystalline silicon solar cells. Solar Energy Materials and Solar Cells 251 (March). doi:10.1016/j.solmat.2022.112143.
   Google Scholar
• Reyes-Urrutia, A., J. Pablo Capossio, C. Venier, E. Torres, R. Rodriguez, and G. Mazza. 2023. Artificial neural network prediction of minimum fluidization velocity for mixtures of biomass and inert solid particles. Fluids. 8(4): doi:10.3390/fluids8040128.
   Web of Science ®Google Scholar
• Schilling, M. A., and M. Esmundo. 2009. Technology S-Curves in renewable energy alternatives: Analysis and implications for industry and government. Energy Policy 37 (5):1767–81. doi:10.1016/j.enpol.2009.01.004.
   Web of Science ®Google Scholar
• Sharma, V., and S. S. Chandel. 2013. Performance and degradation analysis for long term reliability of solar photovoltaic systems: A review. Renewable and Sustainable Energy Reviews 27:753–67. doi:10.1016/j.rser.2013.07.046.
   Web of Science ®Google Scholar
• Snaith, H. J., and P. Hacke. 2018. Enabling reliability assessments of pre-commercial perovskite photovoltaics with lessons learned from industrial standards. Nature Energy 3: 459–65. doi:10.1038/s41560-018-0174-4.
   Web of Science ®Google Scholar
• Sohani, A., H. Sayyaadi, S. Rahman Miremadi, X. Yang, M. Hossein Doranehgard, and S. Nizetic. 2023. Determination of the best air space value for installation of a pv façade technology based on 4e characteristics. Energy. 262 (January). doi:10.1016/j.energy.2022.125386.
   PubMedGoogle Scholar
• Sun, J., Y. Zuo, R. Sun, and L. Zhou. 2021. Research on the conversion efficiency and preparation technology of monocrystalline silicon cells based on statistical distribution. Sustainable Energy Technologies and Assessments. 47 (October). doi:10.1016/j.seta.2021.101482.
   Google Scholar
• Tang, Q., X. Wang, P. Yang, and B. He. 2016. A solar cell that is triggered by sun and rain. Angewandte Chemie International Edition 55 (17):5243–46. doi:https://doi.org/10.1002/anie.201602114.
   PubMed Web of Science ®Google Scholar
• Torres, J. P. N., S. K. Nashih, C. A. F. Fernandes, and J. C. Leite. 2018. The effect of shading on photovoltaic solar panels. Energy Systems. 9 (1):195–208. doi:10.1007/s12667-016-0225-5.
   Google Scholar
• Wang, H., A. Wang, H. Yang, and D. Song. 2016. Analysis of the thermal stress for combined electrode of soldered crystalline silicon solar cells under temperature field. International Journal of Photoenergy 2016:1–7. doi:10.1155/2016/5306925.
   Web of Science ®Google Scholar
• Wendlandt, S., A. Drobisch, T. Buseth, S. Krauter, and P. Grunow. 2010. Hot spot risk analysis on silicon cell modules. 5th World Conference on Photovoltaic Energy Conversion, Valencia, Spain, 4002–4006.
   Google Scholar
• Yaghoubirad, M., N. Azizi, A. Ahmadi, Z. Zarei. 2022. Performance assessment of a solar pv module for different climate classifications based on energy, exergy, economic and environmental parameters. Energy Reports 8:68–84. doi:10.1016/j.egyr.2022.12.070.
   Google Scholar
• Yang, H., F. Wang, H. Wang, J. Chang, D. Song, and C. Su. 2017. Performance deterioration of P-Type single crystalline silicon solar modules affected by potential induced degradation in photovoltaic power plant. Microelectronics Reliability 72:18–23. doi:10.1016/j.microrel.2017.03.017.
   Web of Science ®Google Scholar
• Zabaleta, R., E. Sánchez, P. Fabani, G. Mazza, and R. Rodriguez. 2023. Almond shell biochar: characterization and application in soilless cultivation of eruca sativa. In Biomass conversion and biorefinery. Springer Science and Business Media Deutschland GmbH. doi:10.1007/s13399-023-04002-5.
   Google Scholar
• Zalazar-Garcia, D., M. Celia Román, A. Fernandez, D. Asensio, X. Zhang, M. Paula Fabani, R. Rodriguez, and G. Mazza. 2022. Exergy, energy, and sustainability assessments applied to rsm optimization of integrated convective air-drying with pretreatments to improve the nutritional quality of pumpkin seeds. Sustainable Energy Technologies and Assessments. 49 (February). doi:10.1016/j.seta.2021.101763.
   Google Scholar