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International Journal of Photoenergy
Volume 2014, Article ID 193083, 12 pages
http://dx.doi.org/10.1155/2014/193083
Research Article

Artificial Neural Networks to Predict the Power Output of a PV Panel

DEIM Università degli studi di Palermo, Viale Delle Scienze, Edificio 9, 90128 Palermo, Italy

Received 28 May 2013; Accepted 29 November 2013; Published 23 January 2014

Academic Editor: David Worrall

Copyright © 2014 Valerio Lo Brano et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [18 citations]

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  • Muhammad Mazhar Abbas, Mohamed A. Tawhid, Khalid Saleem, Zia Muhammad, Nazar Abbas Saqib, Hafiz Malik, and Hasan Mahmood, “Solar Energy Harvesting and Management in Wireless Sensor Networks,” International Journal of Distributed Sensor Networks, vol. 2014, pp. 1–8, 2014. View at Publisher · View at Google Scholar
  • Yuan-Kang Wu, Chao-Rong Chen, and Hasimah Abdul Rahman, “A Novel Hybrid Model for Short-Term Forecasting in PV Power Generation,” International Journal of Photoenergy, vol. 2014, pp. 1–9, 2014. View at Publisher · View at Google Scholar
  • Ying-Yi Hong, Faa-Jeng Lin, and Fu-Yuan Hsu, “Enhanced Particle Swarm Optimization-Based Feeder Reconfiguration Considering Uncertain Large Photovoltaic Powers and Demands,” International Journal of Photoenergy, vol. 2014, pp. 1–10, 2014. View at Publisher · View at Google Scholar
  • Ammar Mohammed Ameen, Jagadeesh Pasupuleti, and Tamer Khatib, “Modeling of photovoltaic array output current based on actual performance using artificial neural networks,” Journal of Renewable and Sustainable Energy, vol. 7, no. 5, pp. 053107, 2015. View at Publisher · View at Google Scholar
  • Ireneusz Jablonski, “Smart Transducer Interface-From Networked On-Site Optimization of Energy Balance in Research-Demonstrative Office Building to Smart City Conception,” Ieee Sensors Journal, vol. 15, no. 5, 2015. View at Publisher · View at Google Scholar
  • Sebastijan Seme, Joze Pozun, Bojan Stumberger, and Miralem Hadziselimovic, “Energy Production of Different Types and Orientations of Photovoltaic Systems Under Outdoor Conditions,” Journal Of Solar Energy Engineering-Transactions Of The Asme, vol. 137, no. 2, 2015. View at Publisher · View at Google Scholar
  • N. Aste, C. Del Pero, and F. Leonforte, “The first Italian BIPV project: Case study and long-term performance analysis,” Solar Energy, vol. 134, pp. 340–352, 2016. View at Publisher · View at Google Scholar
  • Leopold Mba, Pierre Meukam, and Alexis Kemajou, “Application of artificial neural network for predicting hourly indoor air temperature and relative humidity in modern building in humid region,” Energy and Buildings, vol. 121, pp. 32–42, 2016. View at Publisher · View at Google Scholar
  • Ibrahim A Ibrahim, Tamer Khatib, Azah Mohamed, and Wilfried Elmenreich, “Modeling of the output current of a photovoltaic grid-connected system using random forests technique,” Energy Exploration & Exploitation, pp. 014459871772364, 2017. View at Publisher · View at Google Scholar
  • A.J. Aristizábal, and C.A. Páez, “Experimental investigation of the performance of 6 kW BIPV system applied in laboratory building,” Energy and Buildings, 2017. View at Publisher · View at Google Scholar
  • Marco Beccali, Giuseppina Ciulla, Valerio Lo Brano, Alessandra Galatioto, and Marina Bonomolo, “Artificial neural network decision support tool for assessment of the energy performance and the refurbishment actions for the non-residential building stock in Southern Italy,” Energy, 2017. View at Publisher · View at Google Scholar
  • Hisashi Takeda, “Short-term ensemble forecast for purchased photovoltaic generation,” Solar Energy, vol. 149, pp. 176–187, 2017. View at Publisher · View at Google Scholar
  • Kian Jazayeri, Moein Jazayeri, and Sener Uysal, “Artificial neural network-based all-sky power estimation and fault detection in photovoltaic modules,” Journal of Photonics for Energy, vol. 7, no. 2, 2017. View at Publisher · View at Google Scholar
  • Edison Banguero, Andrés Julián Aristizábal, and William Murillo, “A Verification Study for Grid-Connected 20 kW Solar PV System Operating in Chocó, Colombia,” Energy Procedia, vol. 141, pp. 96–101, 2017. View at Publisher · View at Google Scholar
  • Sebastijan Seme, Bojan Štumberger, Andrzej Krawczyk, Ewa Łada Tondyra, and Miralem Hadžiselimović, “The efficiency of different orientations of photovoltaic systems,” Przeglad Elektrotechniczny, vol. 93, no. 1, pp. 201–204, 2017. View at Publisher · View at Google Scholar
  • O. Nait Mensour, S. Bouaddi, B. Abnay, B. Hlimi, and A. Ihlal, “Mapping and Estimation of Monthly Global Solar Irradiation in Different Zones in Souss-Massa Area, Morocco, Using Artificial Neural Networks,” International Journal of Photoenergy, vol. 2017, pp. 1–19, 2017. View at Publisher · View at Google Scholar
  • M. Beccali, M. Bonomolo, G. Ciulla, and V. Lo Brano, “Assessment of indoor illuminance and study on best photosensors' position for design and commissioning of Daylight Linked Control Systems. A new method based on Artificial Neural Networks,” Energy, 2018. View at Publisher · View at Google Scholar
  • Nivine Attoue, Isam Shahrour, and Rafic Younes, “Smart Building: Use of the Artificial Neural Network Approach for Indoor Temperature Forecasting,” Energies, vol. 11, no. 2, pp. 395, 2018. View at Publisher · View at Google Scholar