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CIVIL & ENVIRONMENTAL ENGINEERING

Assessment of photovoltaic power output using the estimated global solar radiation at Vuwani Science Resources Centre

& | (Reviewing editor)
Article: 2105031 | Received 11 Jul 2021, Accepted 19 Jul 2022, Published online: 21 Aug 2022

References

  • Almorox, J., & Hontoria, C. (2004). Models for obtaining daily global solar radiation with measured air temperature data in Madrid (Spain). Energy Conversion and Management, 45, 209–12.
  • Amekudzi, L. K., Preko, K., Aryee, J., Boakye, O. R., & Quansah, E. (2014). Empirical models for estimating global solar radiation over the Ashanti region of Ghana. Journal of Solar Energy, 1–6.
  • Awara, S., Lynch, M., Pfenninger, S., Schell, K., Sioshansi, I., Staffell, I., Samaan, N., Tindemans, S. H., Wilson, A. L., Zachary, S., Zareipour, H., & Dent, C. J. 2020. Capacity value of solar power and other variable generation. Report of the IEEE PES Task Force on Capacity Value of Solar Power.
  • Ayzvazogluyuksel, O., & Filik, U. B. 2017. Power output forecasting of a solar house by considering different cell temperature methods. Conference paper, Anadolu University, IEE Xplore: 1253–1257.
  • Cheng, C., Duan, S., Cai, T., & Liu, B. (2011). Online 24-h solar power forecasting based on weather type classification using artificial neural network. Solar Energy, 85(11), 2856–2870. https://doi.org/10.1016/j.solener.2011.08.027
  • Ciulla, G., Lo Brano, V., Di Dio, V., & Cipriani, G. (2014). A comparison of different one-diode models for the representation of I-V characteristic of a PV cell. Renewable and Sustainable Energy Reviews, 32, 684–696. https://doi.org/10.1016/j.rser.2014.01.027
  • De Soto, W., Klein, S. A., & Beckman, W. A. (2006). Improvement and validation of a model for photovoltaic array performance. Solar Energy, 80(1), 78–88. https://doi.org/10.1016/j.solener.2005.06.010
  • Ishiharay, A. K., & Poolla, I. C. (2018). Localized solar power prediction based on weather data from local history and global forecasts (pp. 94035). ECE, Carnegie Mellon University (SV), Moffett Field.
  • Khatib, T., Elmenreich, W., & Mohamed, A. (2017). Simplified I-V characteristic tester for photovoltaic modules using a DC-DC boost converter. Sustainability, 9(4), 657. https://doi.org/10.3390/su9040657
  • Maluta, N. E., & Mulaudzi, T. S. (2018). Evaluation of the temperature based models for the estimation of global solar radiation in Pretoria, Gauteng province of South Africa. International Energy Journal, 18, 181–190.
  • Marwal, V. (2012). A comparative study of correlation functions for estimation of monthly mean daily global solar radiation for Jaipur, Rajasthan (India). Indian Journal of Science and Technology, 5(5), 2729–2732. https://doi.org/10.17485/ijst/2012/v5i5.8
  • Miguntanha, N. P., Jayasinghe, M. T. R., & Sendanayake, S. (2015). Predicting solar radiation for tropical islands from rainfall data. Journal of Urban and Environmental Engineering, 9, 109–118.
  • Ramli, A., Prasetyono, E., Wicaksana, R. W., Windarko, N. A., Sedraoui, K., & Al-Turki, Y. A. (2016). On the investigation of photovoltaic output power reduction due to dust accumulation and weather conditions. Renewable Energy, 99, 836–844. https://doi.org/10.1016/j.renene.2016.07.063
  • Skoplaki, E., & Palyvos, J. A. (2009). On the temperature dependence of photovoltaic module electrical performance: A review of efficiency/power correlations. Solar Energy, 83(5), 614–624. https://doi.org/10.1016/j.solener.2008.10.008
  • USAid, University of Venda. 2020. Solar Radiometric Data for Public South African Universities Radiometric Network. [Online]. Available: http://sauran.ac.za. [Accessed 22 November 2020]
  • Zhang, Q. (2018). Comparative analysis of global solar radiation models in different regions of China. Advances in Meteorology, 1–22.