Open Access
E3S Web Conf.
Volume 336, 2022
The International Conference on Energy and Green Computing (ICEGC’2021)
Article Number 00021
Number of page(s) 5
Published online 17 January 2022
  1. Alae, Azouzoute, and Ahmed, Alami Merrouni, and Mohammed, Garoum, and El Ghali, Bennouna. (2019) “Soiling Loss of Solar Glass and Mirror Samples in the Region with Arid Climate”. [Google Scholar]
  2. Bouraiou, A.; Hamouda, M.; Chaker, A.; Neçaibia, A.; Mostefaoui, M.; Boutasseta, N.; Ziane, A.; Dabou, R.;Sahouane, N.; Lachtar, S. Experimental investigation of observed defects in crystalline silicon PV modules under outdoor hot dry climatic conditions in Algeria. [Google Scholar]
  3. Klugmann-Radziemska, E. Degradation of electrical performance of a crystalline photovoltaic module due to dust deposition in northern Poland. access : 9 august [Google Scholar]
  4. access : 9 august 2020 [Google Scholar]
  5. access : 10 august 2020. [Google Scholar]
  6. access : 9 august 2020 [Google Scholar]
  7. access : 9 august 2020 [Google Scholar]
  8. 9 august 2020 [Google Scholar]
  9. B. Laarabi, O. May Tzuc, D. Dahlioui, A. Bassam, M. Flota-Banuelos, A. Barhdadi: Artificial neural network modeling and sensitivity analysis for soiling effects on photovoltaic panels in Morocco. [Google Scholar]
  10. Alae Azouzoute, Mostafa Chouitar, Mohammed Garoum, El Ghali Bennounal, Abdellatif Ghennioui: A New PV Soiling Monitoring Device for Optimized Cleaning Strategy. [Google Scholar]
  11. Buerhop-Lutz and Scheuerpflug (2015): Inspecting PV-plants using aerial, drone-mounted infrared thermography system. 3rd Southern African Solar Energy Conference, Kruger National Park, South Africa, 11–13 May 2015 [Google Scholar]
  12. Zamora, R.J.; Dutton, E.G.; Trainer, M.; McKeen, S.A.; Wilczak, J.M.; Hou, Y.-T: The accuracy of solar irradiance calculations used in mesoscale numerical weather prediction. [Google Scholar]
  13. Marquez and Coimbra: Forecasting of global and direct solar irradiance using stochastic learning methods, ground experiments and the NWS database. [Google Scholar]
  14. Alessandro Betti, Maria Luisa Lo Trovato, Fabio Salvatore Leonardi, Giuseppe Leotta, Fabrizio Ruffini, and Ciro Lanzetta: PREDICTIVE MAINTENANCE IN PHOTOVOLTAIC PLANTS WITH A BIG DATA APPROACH. [Google Scholar]
  15. Moreno-Garcia, I.M.; Palacios-Garcia, E.J.; Pallares-Lopez, V.; Santiago, I.; Gonzalez-Redondo, M.J.; Varo-Martinez, M.; Real-Calvo: Real-time monitoring system for a utility-scale photovoltaic power plant [Google Scholar]
  16. Adhya, S.; Saha, D.; Das, A.; Jana, J.; Saha: An IoT based smart solar photovoltaic remote monitoring and control unit. 2nd International Conference on Control, Instrumentation, Energy & Communication (CIEC), Kolkata, India, 28–30 January 2016; pp. 432–436. [Google Scholar]
  17. BOSMAN, Lisa B., LEON-SALAS, Walter D., HUTZEL, William, et al. PV System predictive maintenance: Challenges, current approaches, and opportunities. Energies, 2020, vol. 13, no 6, p. 1398’ [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.