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Artificial neural network-based model for estimating the produced power of a photovoltaic module

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Cited by:

  1. Wang, Yong & He, Xinbo & Zhou, Ying & Luo, Yongxian & Tang, Yanbing & Narayanan, Govindasami, 2024. "A novel structure adaptive grey seasonal model with data reorganization and its application in solar photovoltaic power generation prediction," Energy, Elsevier, vol. 302(C).
  2. Muhammad Hussain & Hussain Al-Aqrabi & Richard Hill, 2022. "Statistical Analysis and Development of an Ensemble-Based Machine Learning Model for Photovoltaic Fault Detection," Energies, MDPI, vol. 15(15), pages 1-14, July.
  3. Blaifi, Sid-ali & Moulahoum, Samir & Taghezouit, Bilal & Saim, Abdelhakim, 2019. "An enhanced dynamic modeling of PV module using Levenberg-Marquardt algorithm," Renewable Energy, Elsevier, vol. 135(C), pages 745-760.
  4. He, Xinbo & Wang, Yong & Zhang, Yuyang & Ma, Xin & Wu, Wenqing & Zhang, Lei, 2022. "A novel structure adaptive new information priority discrete grey prediction model and its application in renewable energy generation forecasting," Applied Energy, Elsevier, vol. 325(C).
  5. Han, Youhua & Liu, Yang & Lu, Shixiang & Basalike, Pie & Zhang, Jili, 2021. "Electrical performance and power prediction of a roll-bond photovoltaic thermal array under dewing and frosting conditions," Energy, Elsevier, vol. 237(C).
  6. Blaifi, Sid-ali & Mellit, Adel & Taghezouit, Bilal & Moulahoum, Samir & Hafdaoui, Hichem, 2025. "A simple non-parametric model for photovoltaic output power prediction," Renewable Energy, Elsevier, vol. 240(C).
  7. Dong, Xiao-Jian & Shen, Jia-Ni & Ma, Zi-Feng & He, Yi-Jun, 2022. "Simultaneous operating temperature and output power prediction method for photovoltaic modules," Energy, Elsevier, vol. 260(C).
  8. Hocaoglu, Fatih Onur & Serttas, Fatih, 2017. "A novel hybrid (Mycielski-Markov) model for hourly solar radiation forecasting," Renewable Energy, Elsevier, vol. 108(C), pages 635-643.
  9. Trigo-González, Mauricio & Batlles, F.J. & Alonso-Montesinos, Joaquín & Ferrada, Pablo & del Sagrado, J. & Martínez-Durbán, M. & Cortés, Marcelo & Portillo, Carlos & Marzo, Aitor, 2019. "Hourly PV production estimation by means of an exportable multiple linear regression model," Renewable Energy, Elsevier, vol. 135(C), pages 303-312.
  10. Huang, Chao & Bensoussan, Alain & Edesess, Michael & Tsui, Kwok L., 2016. "Improvement in artificial neural network-based estimation of grid connected photovoltaic power output," Renewable Energy, Elsevier, vol. 97(C), pages 838-848.
  11. Liu, Zhengguang & Guo, Zhiling & Chen, Qi & Song, Chenchen & Shang, Wenlong & Yuan, Meng & Zhang, Haoran, 2023. "A review of data-driven smart building-integrated photovoltaic systems: Challenges and objectives," Energy, Elsevier, vol. 263(PE).
  12. Christil Pasion & Torrey Wagner & Clay Koschnick & Steven Schuldt & Jada Williams & Kevin Hallinan, 2020. "Machine Learning Modeling of Horizontal Photovoltaics Using Weather and Location Data," Energies, MDPI, vol. 13(10), pages 1-14, May.
  13. Chiacchio, Ferdinando & D’Urso, Diego & Famoso, Fabio & Brusca, Sebastian & Aizpurua, Jose Ignacio & Catterson, Victoria M., 2018. "On the use of dynamic reliability for an accurate modelling of renewable power plants," Energy, Elsevier, vol. 151(C), pages 605-621.
  14. Alfredo Nespoli & Emanuele Ogliari & Sonia Leva & Alessandro Massi Pavan & Adel Mellit & Vanni Lughi & Alberto Dolara, 2019. "Day-Ahead Photovoltaic Forecasting: A Comparison of the Most Effective Techniques," Energies, MDPI, vol. 12(9), pages 1-15, April.
  15. Nabilah Mat Kassim & Sathiswary Santhiran & Ammar Ahmed Alkahtani & Mohammad Aminul Islam & Sieh Kiong Tiong & Mohd Yusrizal Mohd Yusof & Nowshad Amin, 2023. "An Adaptive Decision Tree Regression Modeling for the Output Power of Large-Scale Solar (LSS) Farm Forecasting," Sustainability, MDPI, vol. 15(18), pages 1-12, September.
  16. Sojung Kim & Sumin Kim, 2021. "Performance Estimation Modeling via Machine Learning of an Agrophotovoltaic System in South Korea," Energies, MDPI, vol. 14(20), pages 1-13, October.
  17. Bhatti, Abdul Rauf & Salam, Zainal, 2018. "A rule-based energy management scheme for uninterrupted electric vehicles charging at constant price using photovoltaic-grid system," Renewable Energy, Elsevier, vol. 125(C), pages 384-400.
  18. Qu, Yinpeng & Xu, Jian & Sun, Yuanzhang & Liu, Dan, 2021. "A temporal distributed hybrid deep learning model for day-ahead distributed PV power forecasting," Applied Energy, Elsevier, vol. 304(C).
  19. Fathabadi, Hassan, 2016. "Novel fast dynamic MPPT (maximum power point tracking) technique with the capability of very high accurate power tracking," Energy, Elsevier, vol. 94(C), pages 466-475.
  20. Zhu, Jiebei & Li, Mingrui & Luo, Lin & Zhang, Bidan & Cui, Mingjian & Yu, Lujie, 2023. "Short-term PV power forecast methodology based on multi-scale fluctuation characteristics extraction," Renewable Energy, Elsevier, vol. 208(C), pages 141-151.
  21. Wang, Kejun & Qi, Xiaoxia & Liu, Hongda, 2019. "A comparison of day-ahead photovoltaic power forecasting models based on deep learning neural network," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
  22. Fathabadi, Hassan, 2015. "Lambert W function-based technique for tracking the maximum power point of PV modules connected in various configurations," Renewable Energy, Elsevier, vol. 74(C), pages 214-226.
  23. 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.
  24. Sommerfeldt, Nelson & Madani, Hatef, 2017. "Revisiting the techno-economic analysis process for building-mounted, grid-connected solar photovoltaic systems: Part one – Review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1379-1393.
  25. Abdul Rauf Bhatti & Ahmed Bilal Awan & Walied Alharbi & Zainal Salam & Abdullah S. Bin Humayd & Praveen R. P. & Kankar Bhattacharya, 2021. "An Improved Approach to Enhance Training Performance of ANN and the Prediction of PV Power for Any Time-Span without the Presence of Real-Time Weather Data," Sustainability, MDPI, vol. 13(21), pages 1-18, October.
  26. Fathabadi, Hassan, 2016. "Novel high accurate sensorless dual-axis solar tracking system controlled by maximum power point tracking unit of photovoltaic systems," Applied Energy, Elsevier, vol. 173(C), pages 448-459.
  27. Li, Chenxi & Yang, Yongheng & Spataru, Sergiu & Zhang, Kanjian & Wei, Haikun, 2021. "A robust parametrization method of photovoltaic modules for enhancing one-diode model accuracy under varying operating conditions," Renewable Energy, Elsevier, vol. 168(C), pages 764-778.
  28. Gulin, Marko & Pavlović, Tomislav & Vašak, Mario, 2016. "Photovoltaic panel and array static models for power production prediction: Integration of manufacturers’ and on-line data," Renewable Energy, Elsevier, vol. 97(C), pages 399-413.
  29. Huxley, O.T. & Taylor, J. & Everard, A. & Briggs, J. & Tilley, K. & Harwood, J. & Buckley, A., 2022. "The uncertainties involved in measuring national solar photovoltaic electricity generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
  30. Qu, Jiaqi & Qian, Zheng & Pei, Yan, 2021. "Day-ahead hourly photovoltaic power forecasting using attention-based CNN-LSTM neural network embedded with multiple relevant and target variables prediction pattern," Energy, Elsevier, vol. 232(C).
  31. Wang, Zheng-Xin & Wang, Zhi-Wei & Li, Qin, 2020. "Forecasting the industrial solar energy consumption using a novel seasonal GM(1,1) model with dynamic seasonal adjustment factors," Energy, Elsevier, vol. 200(C).
  32. Korkmaz, Deniz, 2021. "SolarNet: A hybrid reliable model based on convolutional neural network and variational mode decomposition for hourly photovoltaic power forecasting," Applied Energy, Elsevier, vol. 300(C).
  33. Fan, Siyuan & Wang, Yu & Cao, Shengxian & Zhao, Bo & Sun, Tianyi & Liu, Peng, 2022. "A deep residual neural network identification method for uneven dust accumulation on photovoltaic (PV) panels," Energy, Elsevier, vol. 239(PD).
  34. Torres-Ramírez, M. & Elizondo, D. & García-Domingo, B. & Nofuentes, G. & Talavera, D.L., 2015. "Modelling the spectral irradiance distribution in sunny inland locations using an ANN-based methodology," Energy, Elsevier, vol. 86(C), pages 323-334.
  35. Wang, Shinong & Wang, Zheng & Ge, Yuan & Amer, Ragab Ahmed, 2025. "Performance estimator of photovoltaic modules by integrating deep learning network with physical model," Energy, Elsevier, vol. 325(C).
  36. Rajesh, R. & Carolin Mabel, M., 2015. "A comprehensive review of photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 231-248.
  37. Paiho, Satu & Kiljander, Jussi & Sarala, Roope & Siikavirta, Hanne & Kilkki, Olli & Bajpai, Arpit & Duchon, Markus & Pahl, Marc-Oliver & Wüstrich, Lars & Lübben, Christian & Kirdan, Erkin & Schindler,, 2021. "Towards cross-commodity energy-sharing communities – A review of the market, regulatory, and technical situation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
  38. Hussain, Muhammed & Dhimish, Mahmoud & Titarenko, Sofya & Mather, Peter, 2020. "Artificial neural network based photovoltaic fault detection algorithm integrating two bi-directional input parameters," Renewable Energy, Elsevier, vol. 155(C), pages 1272-1292.
  39. Kermadi, Mostefa & Berkouk, El Madjid, 2017. "Artificial intelligence-based maximum power point tracking controllers for Photovoltaic systems: Comparative study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 369-386.
  40. Yadav, Amit Kumar & Chandel, S.S., 2017. "Identification of relevant input variables for prediction of 1-minute time-step photovoltaic module power using Artificial Neural Network and Multiple Linear Regression Models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 955-969.
  41. Nicolás Müller & Samir Kouro & Pericle Zanchetta & Patrick Wheeler & Gustavo Bittner & Francesco Girardi, 2019. "Energy Storage Sizing Strategy for Grid-Tied PV Plants under Power Clipping Limitations," Energies, MDPI, vol. 12(9), pages 1-17, May.
  42. Yadav, Amit Kumar & Sharma, Vikrant & Malik, Hasmat & Chandel, S.S., 2018. "Daily array yield prediction of grid-interactive photovoltaic plant using relief attribute evaluator based Radial Basis Function Neural Network," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2115-2127.
  43. Sharadga, Hussein & Hajimirza, Shima & Balog, Robert S., 2020. "Time series forecasting of solar power generation for large-scale photovoltaic plants," Renewable Energy, Elsevier, vol. 150(C), pages 797-807.
  44. Chao-Rong Chen & Faouzi Brice Ouedraogo & Yu-Ming Chang & Devita Ayu Larasati & Shih-Wei Tan, 2021. "Hour-Ahead Photovoltaic Output Forecasting Using Wavelet-ANFIS," Mathematics, MDPI, vol. 9(19), pages 1-14, October.
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