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Modelling of solar energy potential in Nigeria using an artificial neural network model

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  1. Heo, Jae & Song, Kwonsik & Han, SangUk & Lee, Dong-Eun, 2021. "Multi-channel convolutional neural network for integration of meteorological and geographical features in solar power forecasting," Applied Energy, Elsevier, vol. 295(C).
  2. Ajayi, Oluseyi O, 2013. "Sustainable energy development and environmental protection: Implication for selected states in West Africa," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 532-539.
  3. Njoku, H.O., 2016. "Upper-limit solar photovoltaic power generation: Estimates for 2-axis tracking collectors in Nigeria," Energy, Elsevier, vol. 95(C), pages 504-516.
  4. Paweł Pijarski & Adrian Belowski, 2024. "Application of Methods Based on Artificial Intelligence and Optimisation in Power Engineering—Introduction to the Special Issue," Energies, MDPI, vol. 17(2), pages 1-42, January.
  5. Kisi, Ozgur, 2014. "Modeling solar radiation of Mediterranean region in Turkey by using fuzzy genetic approach," Energy, Elsevier, vol. 64(C), pages 429-436.
  6. Yu, Shiwei & Wei, Yi-Ming & Wang, Ke, 2012. "A PSO–GA optimal model to estimate primary energy demand of China," Energy Policy, Elsevier, vol. 42(C), pages 329-340.
  7. Apfel, Dorothee & Haag, Steffen & Herbes, Carsten, 2021. "Research agendas on renewable energies in the Global South: A systematic literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
  8. WenBo Xiao & Gina Nazario & HuaMing Wu & HuaMing Zhang & Feng Cheng, 2017. "A neural network based computational model to predict the output power of different types of photovoltaic cells," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-8, September.
  9. Deo, Ravinesh C. & Wen, Xiaohu & Qi, Feng, 2016. "A wavelet-coupled support vector machine model for forecasting global incident solar radiation using limited meteorological dataset," Applied Energy, Elsevier, vol. 168(C), pages 568-593.
  10. Ali Jallal, Mohammed & Chabaa, Samira & Zeroual, Abdelouhab, 2020. "A novel deep neural network based on randomly occurring distributed delayed PSO algorithm for monitoring the energy produced by four dual-axis solar trackers," Renewable Energy, Elsevier, vol. 149(C), pages 1182-1196.
  11. Shaddel, Mehdi & Javan, Dawood Seyed & Baghernia, Parisa, 2016. "Estimation of hourly global solar irradiation on tilted absorbers from horizontal one using Artificial Neural Network for case study of Mashhad," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 59-67.
  12. Ugwoke, B. & Gershon, O. & Becchio, C. & Corgnati, S.P. & Leone, P., 2020. "A review of Nigerian energy access studies: The story told so far," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
  13. Gutiérrez-Trashorras, Antonio J. & Villicaña-Ortiz, Eunice & Álvarez-Álvarez, Eduardo & González-Caballín, Juan M. & Xiberta-Bernat, Jorge & Suarez-López, María J., 2018. "Attenuation processes of solar radiation. Application to the quantification of direct and diffuse solar irradiances on horizontal surfaces in Mexico by means of an overall atmospheric transmittance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 93-106.
  14. Li, Huashan & Ma, Weibin & Lian, Yongwang & Wang, Xianlong, 2010. "Estimating daily global solar radiation by day of year in China," Applied Energy, Elsevier, vol. 87(10), pages 3011-3017, October.
  15. 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.
  16. Heo, Jae & Jung, Jaehoon & Kim, Byungil & Han, SangUk, 2020. "Digital elevation model-based convolutional neural network modeling for searching of high solar energy regions," Applied Energy, Elsevier, vol. 262(C).
  17. Matallanas, E. & Castillo-Cagigal, M. & Gutiérrez, A. & Monasterio-Huelin, F. & Caamaño-Martín, E. & Masa, D. & Jiménez-Leube, J., 2012. "Neural network controller for Active Demand-Side Management with PV energy in the residential sector," Applied Energy, Elsevier, vol. 91(1), pages 90-97.
  18. Qin, Jun & Chen, Zhuoqi & Yang, Kun & Liang, Shunlin & Tang, Wenjun, 2011. "Estimation of monthly-mean daily global solar radiation based on MODIS and TRMM products," Applied Energy, Elsevier, vol. 88(7), pages 2480-2489, July.
  19. Hassan, Gasser E. & Youssef, M. Elsayed & Mohamed, Zahraa E. & Ali, Mohamed A. & Hanafy, Ahmed A., 2016. "New Temperature-based Models for Predicting Global Solar Radiation," Applied Energy, Elsevier, vol. 179(C), pages 437-450.
  20. Yu, Shi-wei & Zhu, Ke-jun, 2012. "A hybrid procedure for energy demand forecasting in China," Energy, Elsevier, vol. 37(1), pages 396-404.
  21. Elham Alzain & Shaha Al-Otaibi & Theyazn H. H. Aldhyani & Ali Saleh Alshebami & Mohammed Amin Almaiah & Mukti E. Jadhav, 2023. "Revolutionizing Solar Power Production with Artificial Intelligence: A Sustainable Predictive Model," Sustainability, MDPI, vol. 15(10), pages 1-21, May.
  22. Zou, Ling & Wang, Lunche & Xia, Li & Lin, Aiwen & Hu, Bo & Zhu, Hongji, 2017. "Prediction and comparison of solar radiation using improved empirical models and Adaptive Neuro-Fuzzy Inference Systems," Renewable Energy, Elsevier, vol. 106(C), pages 343-353.
  23. Yadav, Amit Kumar & Malik, Hasmat & Chandel, S.S., 2015. "Application of rapid miner in ANN based prediction of solar radiation for assessment of solar energy resource potential of 76 sites in Northwestern India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1093-1106.
  24. Notton, Gilles & Paoli, Christophe & Vasileva, Siyana & Nivet, Marie Laure & Canaletti, Jean-Louis & Cristofari, Christian, 2012. "Estimation of hourly global solar irradiation on tilted planes from horizontal one using artificial neural networks," Energy, Elsevier, vol. 39(1), pages 166-179.
  25. Almorox, J. & Hontoria, C. & Benito, M., 2011. "Models for obtaining daily global solar radiation with measured air temperature data in Madrid (Spain)," Applied Energy, Elsevier, vol. 88(5), pages 1703-1709, May.
  26. 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.
  27. Olanrewaju, O.A. & Jimoh, A.A. & Kholopane, P.A., 2013. "Assessing the energy potential in the South African industry: A combined IDA-ANN-DEA (Index Decomposition Analysis-Artificial Neural Network-Data Envelopment Analysis) model," Energy, Elsevier, vol. 63(C), pages 225-232.
  28. Baklacioglu, Tolga & Turan, Onder & Aydin, Hakan, 2015. "Dynamic modeling of exergy efficiency of turboprop engine components using hybrid genetic algorithm-artificial neural networks," Energy, Elsevier, vol. 86(C), pages 709-721.
  29. Rohani, Abbas & Taki, Morteza & Abdollahpour, Masoumeh, 2018. "A novel soft computing model (Gaussian process regression with K-fold cross validation) for daily and monthly solar radiation forecasting (Part: I)," Renewable Energy, Elsevier, vol. 115(C), pages 411-422.
  30. 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.
  31. von Grabe, Jörn, 2016. "Potential of artificial neural networks to predict thermal sensation votes," Applied Energy, Elsevier, vol. 161(C), pages 412-424.
  32. Candra Saigustia & Paweł Pijarski, 2023. "Time Series Analysis and Forecasting of Solar Generation in Spain Using eXtreme Gradient Boosting: A Machine Learning Approach," Energies, MDPI, vol. 16(22), pages 1-14, November.
  33. Hocaoglu, Fatih Onur & Karanfil, Fatih, 2013. "A time series-based approach for renewable energy modeling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 204-214.
  34. Bahrami, Arian & Okoye, Chiemeka Onyeka & Atikol, Ugur, 2017. "Technical and economic assessment of fixed, single and dual-axis tracking PV panels in low latitude countries," Renewable Energy, Elsevier, vol. 113(C), pages 563-579.
  35. Zarzo, Manuel & Martí, Pau, 2011. "Modeling the variability of solar radiation data among weather stations by means of principal components analysis," Applied Energy, Elsevier, vol. 88(8), pages 2775-2784, August.
  36. Wu, Qunli & Peng, Chenyang, 2017. "A hybrid BAG-SA optimal approach to estimate energy demand of China," Energy, Elsevier, vol. 120(C), pages 985-995.
  37. Yeo, In-Ae & Yee, Jurng-Jae, 2014. "A proposal for a site location planning model of environmentally friendly urban energy supply plants using an environment and energy geographical information system (E-GIS) database (DB) and an artifi," Applied Energy, Elsevier, vol. 119(C), pages 99-117.
  38. Liu, Luyao & Zhao, Yi & Chang, Dongliang & Xie, Jiyang & Ma, Zhanyu & Sun, Qie & Yin, Hongyi & Wennersten, Ronald, 2018. "Prediction of short-term PV power output and uncertainty analysis," Applied Energy, Elsevier, vol. 228(C), pages 700-711.
  39. Olukan, Tuza A. & Santos, Sergio & Al Ghaferi, Amal A. & Chiesa, Matteo, 2022. "Development of a solar nano-grid for meeting the electricity supply shortage in developing countries (Nigeria as a case study)," Renewable Energy, Elsevier, vol. 181(C), pages 640-652.
  40. Mohamed A. Ali & Ashraf Elsayed & Islam Elkabani & Mohammad Akrami & M. Elsayed Youssef & Gasser E. Hassan, 2023. "Optimizing Artificial Neural Networks for the Accurate Prediction of Global Solar Radiation: A Performance Comparison with Conventional Methods," Energies, MDPI, vol. 16(17), pages 1-30, August.
  41. Okoye, Chiemeka Onyeka & Taylan, Onur & Baker, Derek K., 2016. "Solar energy potentials in strategically located cities in Nigeria: Review, resource assessment and PV system design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 550-566.
  42. Alamdari, Pouria & Nematollahi, Omid & Alemrajabi, Ali Akbar, 2013. "Solar energy potentials in Iran: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 778-788.
  43. Alonso-Montesinos, J. & Batlles, F.J., 2015. "The use of a sky camera for solar radiation estimation based on digital image processing," Energy, Elsevier, vol. 90(P1), pages 377-386.
  44. Fadare, D.A., 2010. "The application of artificial neural networks to mapping of wind speed profile for energy application in Nigeria," Applied Energy, Elsevier, vol. 87(3), pages 934-942, March.
  45. Giwa, Adewale & Alabi, Adetunji & Yusuf, Ahmed & Olukan, Tuza, 2017. "A comprehensive review on biomass and solar energy for sustainable energy generation in Nigeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 620-641.
  46. Ouammi, Ahmed & Zejli, Driss & Dagdougui, Hanane & Benchrifa, Rachid, 2012. "Artificial neural network analysis of Moroccan solar potential," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4876-4889.
  47. Jiandong Liu & Tao Pan & Deliang Chen & Xiuji Zhou & Qiang Yu & Gerald N. Flerchinger & De Li Liu & Xintong Zou & Hans W. Linderholm & Jun Du & Dingrong Wu & Yanbo Shen, 2017. "An Improved Ångström-Type Model for Estimating Solar Radiation over the Tibetan Plateau," Energies, MDPI, vol. 10(7), pages 1-28, July.
  48. Okoye, Chiemeka Onyeka & Bahrami, Arian & Atikol, Ugur, 2018. "Evaluating the solar resource potential on different tracking surfaces in Nigeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1569-1581.
  49. Nosipho Zwane & Henerica Tazvinga & Christina Botai & Miriam Murambadoro & Joel Botai & Jaco de Wit & Brighton Mabasa & Siphamandla Daniel & Tafadzwanashe Mabhaudhi, 2022. "A Bibliometric Analysis of Solar Energy Forecasting Studies in Africa," Energies, MDPI, vol. 15(15), pages 1-23, July.
  50. Teke, Ahmet & Yıldırım, H. Başak & Çelik, Özgür, 2015. "Evaluation and performance comparison of different models for the estimation of solar radiation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 1097-1107.
  51. Kılıç, Fatih & Yılmaz, İbrahim Halil & Kaya, Özge, 2021. "Adaptive co-optimization of artificial neural networks using evolutionary algorithm for global radiation forecasting," Renewable Energy, Elsevier, vol. 171(C), pages 176-190.
  52. Hussain, Sajid & Al-Alili, Ali, 2016. "A new approach for model validation in solar radiation using wavelet, phase and frequency coherence analysis," Applied Energy, Elsevier, vol. 164(C), pages 639-649.
  53. Jabar H. Yousif & Hussein A. Kazem & John Boland, 2017. "Predictive Models for Photovoltaic Electricity Production in Hot Weather Conditions," Energies, MDPI, vol. 10(7), pages 1-19, July.
  54. Almonacid, F. & Fernández, Eduardo F. & Rodrigo, P. & Pérez-Higueras, P.J. & Rus-Casas, C., 2013. "Estimating the maximum power of a High Concentrator Photovoltaic (HCPV) module using an Artificial Neural Network," Energy, Elsevier, vol. 53(C), pages 165-172.
  55. Kebir, Anouer & Woodward, Lyne & Akhrif, Ouassima, 2019. "Real-time optimization of renewable energy sources power using neural network-based anticipative extremum-seeking control," Renewable Energy, Elsevier, vol. 134(C), pages 914-926.
  56. 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.
  57. Minglu Ma & Zhuangzhuang Wang, 2019. "Prediction of the Energy Consumption Variation Trend in South Africa based on ARIMA, NGM and NGM-ARIMA Models," Energies, MDPI, vol. 13(1), pages 1-15, December.
  58. Dahmani, Kahina & Notton, Gilles & Voyant, Cyril & Dizene, Rabah & Nivet, Marie Laure & Paoli, Christophe & Tamas, Wani, 2016. "Multilayer Perceptron approach for estimating 5-min and hourly horizontal global irradiation from exogenous meteorological data in locations without solar measurements," Renewable Energy, Elsevier, vol. 90(C), pages 267-282.
  59. Bikhtiyar Ameen & Heiko Balzter & Claire Jarvis & James Wheeler, 2019. "Modelling Hourly Global Horizontal Irradiance from Satellite-Derived Datasets and Climate Variables as New Inputs with Artificial Neural Networks," Energies, MDPI, vol. 12(1), pages 1-28, January.
  60. Shubham Gupta & Amit Kumar Singh & Sachin Mishra & Pradeep Vishnuram & Nagaraju Dharavat & Narayanamoorthi Rajamanickam & Ch. Naga Sai Kalyan & Kareem M. AboRas & Naveen Kumar Sharma & Mohit Bajaj, 2023. "Estimation of Solar Radiation with Consideration of Terrestrial Losses at a Selected Location—A Review," Sustainability, MDPI, vol. 15(13), pages 1-29, June.
  61. Jose Manuel Barrera & Alejandro Reina & Alejandro Maté & Juan Carlos Trujillo, 2020. "Solar Energy Prediction Model Based on Artificial Neural Networks and Open Data," Sustainability, MDPI, vol. 12(17), pages 1-20, August.
  62. Yadav, Amit Kumar & Malik, Hasmat & Chandel, S.S., 2014. "Selection of most relevant input parameters using WEKA for artificial neural network based solar radiation prediction models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 509-519.
  63. Aliyu, Abubakar Sadiq & Dada, Joseph O. & Adam, Ibrahim Khalil, 2015. "Current status and future prospects of renewable energy in Nigeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 336-346.
  64. Amrouche, Badia & Le Pivert, Xavier, 2014. "Artificial neural network based daily local forecasting for global solar radiation," Applied Energy, Elsevier, vol. 130(C), pages 333-341.
  65. Lukač, Niko & Žlaus, Danijel & Seme, Sebastijan & Žalik, Borut & Štumberger, Gorazd, 2013. "Rating of roofs’ surfaces regarding their solar potential and suitability for PV systems, based on LiDAR data," Applied Energy, Elsevier, vol. 102(C), pages 803-812.
  66. Gassar, Abdo Abdullah Ahmed & Cha, Seung Hyun, 2021. "Review of geographic information systems-based rooftop solar photovoltaic potential estimation approaches at urban scales," Applied Energy, Elsevier, vol. 291(C).
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