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Methodology for predicting sequences of mean monthly clearness index and daily solar radiation data in remote areas: Application for sizing a stand-alone PV system

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  1. Khatib, Tamer & Mohamed, Azah & Sopian, K., 2012. "A review of solar energy modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 2864-2869.
  2. Achour, Lazhar & Bouharkat, Malek & Assas, Ouarda & Behar, Omar, 2017. "Hybrid model for estimating monthly global solar radiation for the Southern of Algeria: (Case study: Tamanrasset, Algeria)," Energy, Elsevier, vol. 135(C), pages 526-539.
  3. Djafer, D. & Irbah, A. & Zaiani, M., 2017. "Identification of clear days from solar irradiance observations using a new method based on the wavelet transform," Renewable Energy, Elsevier, vol. 101(C), pages 347-355.
  4. Ayodele, T.R. & Ogunjuyigbe, A.S.O., 2015. "Prediction of monthly average global solar radiation based on statistical distribution of clearness index," Energy, Elsevier, vol. 90(P2), pages 1733-1742.
  5. Kheradmanda, Saeid & Nematollahi, Omid & Ayoobia, Ahmad Reza, 2016. "Clearness index predicting using an integrated artificial neural network (ANN) approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1357-1365.
  6. Voyant, Cyril & Muselli, Marc & Paoli, Christophe & Nivet, Marie-Laure, 2013. "Hybrid methodology for hourly global radiation forecasting in Mediterranean area," Renewable Energy, Elsevier, vol. 53(C), pages 1-11.
  7. Gairaa, Kacem & Voyant, Cyril & Notton, Gilles & Benkaciali, Saïd & Guermoui, Mawloud, 2022. "Contribution of ordinal variables to short-term global solar irradiation forecasting for sites with low variabilities," Renewable Energy, Elsevier, vol. 183(C), pages 890-902.
  8. Rodrigues, Eugénio & Gomes, Álvaro & Gaspar, Adélio Rodrigues & Henggeler Antunes, Carlos, 2018. "Estimation of renewable energy and built environment-related variables using neural networks – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 959-988.
  9. Baños, R. & Manzano-Agugliaro, F. & Montoya, F.G. & Gil, C. & Alcayde, A. & Gómez, J., 2011. "Optimization methods applied to renewable and sustainable energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(4), pages 1753-1766, May.
  10. Khalil, Samy A. & Shaffie, A.M., 2016. "Evaluation of transposition models of solar irradiance over Egypt," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 105-119.
  11. Himri, Y. & Malik, Arif S. & Boudghene Stambouli, A. & Himri, S. & Draoui, B., 2009. "Review and use of the Algerian renewable energy for sustainable development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(6-7), pages 1584-1591, August.
  12. Kasaeian, Alibakhsh & Rajaee, Fatemeh & Yan, Wei-Mon, 2019. "Osmotic desalination by solar energy: A critical review," Renewable Energy, Elsevier, vol. 134(C), pages 1473-1490.
  13. Benghanem, Mohamed & Mellit, Adel, 2010. "Radial Basis Function Network-based prediction of global solar radiation data: Application for sizing of a stand-alone photovoltaic system at Al-Madinah, Saudi Arabia," Energy, Elsevier, vol. 35(9), pages 3751-3762.
  14. Sharifzadeh, Mahdi & Sikinioti-Lock, Alexandra & Shah, Nilay, 2019. "Machine-learning methods for integrated renewable power generation: A comparative study of artificial neural networks, support vector regression, and Gaussian Process Regression," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 513-538.
  15. Suganthi, L. & Iniyan, S. & Samuel, Anand A., 2015. "Applications of fuzzy logic in renewable energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 585-607.
  16. Mellit, Adel & Kalogirou, Soteris A. & Drif, Mahmoud, 2010. "Application of neural networks and genetic algorithms for sizing of photovoltaic systems," Renewable Energy, Elsevier, vol. 35(12), pages 2881-2893.
  17. Mohanty, Sthitapragyan & Patra, Prashanta Kumar & Sahoo, Sudhansu Sekhar, 2016. "Prediction and application of solar radiation with soft computing over traditional and conventional approach – A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 778-796.
  18. Karabacak, Kerim & Cetin, Numan, 2014. "Artificial neural networks for controlling wind–PV power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 804-827.
  19. Dahmani, Kahina & Dizene, Rabah & Notton, Gilles & Paoli, Christophe & Voyant, Cyril & Nivet, Marie Laure, 2014. "Estimation of 5-min time-step data of tilted solar global irradiation using ANN (Artificial Neural Network) model," Energy, Elsevier, vol. 70(C), pages 374-381.
  20. Işık, Erdem & Inallı, Mustafa, 2018. "Artificial neural networks and adaptive neuro-fuzzy inference systems approaches to forecast the meteorological data for HVAC: The case of cities for Turkey," Energy, Elsevier, vol. 154(C), pages 7-16.
  21. Nasiri, Reza & Radan, Ahmad, 2011. "Adaptive decoupled control of 4-leg voltage-source inverters for standalone photovoltaic systems: Adjusting transient state response," Renewable Energy, Elsevier, vol. 36(10), pages 2733-2741.
  22. Kaplani, E. & Kaplanis, S. & Mondal, S., 2018. "A spatiotemporal universal model for the prediction of the global solar radiation based on Fourier series and the site altitude," Renewable Energy, Elsevier, vol. 126(C), pages 933-942.
  23. Nasiri, Reza & Radan, Ahmad, 2011. "Pole-placement control of 4-leg voltage-source inverters for standalone photovoltaic systems: Considering digital delays," Renewable Energy, Elsevier, vol. 36(2), pages 858-865.
  24. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.
  25. Roumpakias, Elias & Zogou, Olympia & Stamatelos, Anastassios, 2015. "Correlation of actual efficiency of photovoltaic panels with air mass," Renewable Energy, Elsevier, vol. 74(C), pages 70-77.
  26. Su, Yan & Chan, Lai-Cheong & Shu, Lianjie & Tsui, Kwok-Leung, 2012. "Real-time prediction models for output power and efficiency of grid-connected solar photovoltaic systems," Applied Energy, Elsevier, vol. 93(C), pages 319-326.
  27. Kaplani, E. & Kaplanis, S., 2012. "A stochastic simulation model for reliable PV system sizing providing for solar radiation fluctuations," Applied Energy, Elsevier, vol. 97(C), pages 970-981.
  28. Nourhane Merabet & Lina Chouichi & Kaouther Kerboua, 2022. "Numerical design and simulation of a thermodynamic solar solution for a pilot residential building at the edge of the sun-belt region," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(11), pages 12582-12608, November.
  29. Khalil, Samy A. & Shaffie, A.M., 2013. "A comparative study of total, direct and diffuse solar irradiance by using different models on horizontal and inclined surfaces for Cairo, Egypt," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 853-863.
  30. Zendehboudi, Sohrab & Rezaei, Nima & Lohi, Ali, 2018. "Applications of hybrid models in chemical, petroleum, and energy systems: A systematic review," Applied Energy, Elsevier, vol. 228(C), pages 2539-2566.
  31. Zina Boussaada & Octavian Curea & Ahmed Remaci & Haritza Camblong & Najiba Mrabet Bellaaj, 2018. "A Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the Prediction of the Daily Direct Solar Radiation," Energies, MDPI, vol. 11(3), pages 1-21, March.
  32. Nasiri, Reza & Radan, Ahmad, 2011. "Adaptive pole-placement control of 4-leg voltage-source inverters for standalone photovoltaic systems," Renewable Energy, Elsevier, vol. 36(7), pages 2032-2042.
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