Open Access
Issue
E3S Web Conf.
Volume 477, 2024
International Conference on Smart Technologies and Applied Research (STAR'2023)
Article Number 00088
Number of page(s) 9
DOI https://doi.org/10.1051/e3sconf/202447700088
Published online 16 January 2024
  1. Dengjia Wanga, Jin Liua Yanfeng Liua Yingying Wanga Bojia Lib, Jiaping Liua, Evaluation of the performance of an improved solar air heater with “S” Shaped ribs with gap, Solar Energy 195 (2020) 89–101, June 2019 [Google Scholar]
  2. V.S. Hansa, R.P.Saini b, J.S.Saini c, Heat transfer and friction factor correlations for a solar air heaterDuct roughened artificially with multiple v- ribs, Solar Energy 84 (2010) 898–911 [CrossRef] [Google Scholar]
  3. Istvan Fekete a, Istvan Farkas b, Numerical and experimental study of building integrated solar tile Collectors, Renewable Energy (2018) 1-11 [Google Scholar]
  4. Satyender Singh, Experimental and numerical investigations of a single and double pass Porous serpentine wavy wiremesh packed bed solar air heater, Renewable Energy 145 (2020) 1361-1387 [CrossRef] [Google Scholar]
  5. Ghritlahre, H.K. and Verma, M., 2021. Solar air heaters performance prediction using multi-layer perceptron neural network– A systematic review. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, pp.1-18. [Google Scholar]
  6. Ghritlahre, H.K. and Prasad, R.K., 2018. Exergetic Performance Prediction of a Roughened Solar Air Heater Using Artificial Neural Network. Strojniski Vestnik/Journal of Mechanical Engineering, 64(3). [Google Scholar]
  7. J. S. R. Jang., “ANFIS: Adaptive-Network-based Fuzzy Inference Systems,” IEEE Transactions on Systems, Man, and Cybernetics, vol. 23(3), pp. 665-685, May 1993. [CrossRef] [Google Scholar]
  8. Karuppusamy, Dr P. “Synchronization of Reactive Power in Solar Based DG and Voltage Regulated Elements Using Stochastic Optimization Technique.” Journal of Electrical Engineering and Automation 2, no. 1 (2020): 50-59. [CrossRef] [Google Scholar]
  9. Elbreki AM, Muftah AF, Sopian K, Jarimi H, Fazlizan A, Ibrahim A. Experimental and economic analysis of passive cooling PV module using fins and planar reflector. Case Stud Therm Eng. 2021;23. doi: 10.1016/j.csite.2020.100801 [Google Scholar]
  10. Farhan AA, Hasan DJ. An experimental investigation to augment the efficiency of photovoltaic panels by using longitudinal fins. Heat Transf. 2021;50(2):1748-1757. doi: 10.1002/htj.21951 [CrossRef] [Google Scholar]
  11. Parkunam, N., Pandiyan, L., Navaneethakrishnan, G., Arul, S. and Vijayan, V., 2020. Experimental analysis on passive cooling of flat photovoltaic panel with heat sink and wick structure. Energy Sources Part A-recovery Utilization and Environmental Effects, 42(6), pp.653-663. [CrossRef] [Google Scholar]
  12. Mohamed Sharaf, A.S. Huzayyin Mohamed, S. Yousef, Performance enhancement of photovoltaic cells using phase change material (PCM) in winter, Alexandria Engineering Journal, Volume 61, Issue 6, June 2022, Pages 4229-4239 [CrossRef] [Google Scholar]
  13. Savvakis N, Dialyna E, Tsoutsos T. Investigation of the operational performance and efficiency of an alternative PV + PCM concept. Sol Energy. 2020;211:1283-1300. doi: 10.1016/j.solener.2020.10.053 [CrossRef] [Google Scholar]
  14. Sangeetha M, Manigandan S, Ashok B, Brindhadevi K, Pugazhendhi A. Experimental investigation of nanofluid based photovoltaic thermal (PV/T) system for superior electrical efficiency and hydrogen production. Fuel. 2021;286. doi: 10.1016/j.fuel.2020.119422 [Google Scholar]
  15. Ebaid MSY, Al-busoul M, Ghrair AM. Performance enhancement of photovoltaic panels using two types of nanofluids. Heat Transf. 2020;49(5): 2789-2812. doi: 10.1002/htj.21745 [CrossRef] [Google Scholar]
  16. Abdelrazik AS, Saidur R, Al-Sulaiman FA. Investigation of the performance of a hybrid PV/thermal system using water/silver nanofluid-based optical filter. Energy. 2021;215. doi: 10.1016/j.energy.2020.119172 [Google Scholar]
  17. Mustafa U, Qeays IA, BinArif MS, Yahya SM, Shahrin S Bin. Efficiency improvement of the solar PV-system using nanofluid and developed inverter topology. Energy Sources, Part A Recover Util Environ Eff. Published online 2020. doi: 10.1080/15567036.2020.1808119 [Google Scholar]
  18. Sagayaraj, A.S., Devi, T.K. and Umadevi, S., 2021. Prediction of Sulfur Content in Copra Using Machine Learning Algorithm. Applied Artificial Intelligence, 35(15), pp.2228-2245. [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.