EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 564 (2024) E3S Web Conf., 564 (2024) 09003 References
Open Access
Issue
E3S Web Conf.
Volume 564, 2024
International Conference on Power Generation and Renewable Energy Sources (ICPGRES-2024)
Article Number 09003
Number of page(s) 16
Section Maximum Power Point Tracking
DOI https://doi.org/10.1051/e3sconf/202456409003
Published online 06 September 2024
  1. R. Abdul-Kalaam, S. Muyeen, A. Al-Durra. Review of maximum power point tracking techniques for photovoltaic system. Glob. J. Control Eng. Technol, 2, 8-18, (2016) [Google Scholar]
  2. K. Ahmad El, A.R. Nasrudin, S. Jeyraj, M. NasirUddin.Fuzzy logic controller-based SEPIC converter for maximum power point tracking. IEEE Trans. Ind. Appl. 50, 4, 2349–2358, (2014) [CrossRef] [Google Scholar]
  3. J. Ahmed, Z. Salam. A critical evaluation on maximum power point tracking methods for partial shading in PV systems. Renew. Sustain. Energy Rev. 47, 933–953, (2015) [CrossRef] [Google Scholar]
  4. A. Badis, M.N. Mansouri, M.H. Boujmil.A genetic algorithm optimized MPPT controller for a PV system with DC-DC boost converter. In: Proc. of International Conference on Engineering &, Monastir, 1-6, (2017) [Google Scholar]
  5. M. Bahrami, M. Zandi, R. Gavagsaz, B. Nahid-Mobarakeh, S. Pierfederici. A new hybrid method of MPPT for photovoltaic systems based on FLC and three point-weight methods. In IEEE 7th Power Electronics and Drive Systems Technologies Conference (PEDSTC), 446-450, (2016) [Google Scholar]
  6. F. Belhachat, C. Larbes. Comprehensive review on global maximum power point tracking techniques for PV systems subjected to partial shading conditions. Sol. Energy 183, 476–500, (2019) [CrossRef] [Google Scholar]
  7. H. Bellia, R. Youcef, M. Fatima. A detailed modeling of photovoltaic module using MATLAB. NRIAG J. Astron. Geophys. 3, 1, 53–61, (2014) [CrossRef] [Google Scholar]
  8. A.S. Benyoucefa, A. Chouderb, K. Karaa, S. Silvestrec, O.A. Sahedaa. Artificial bee colony-based algorithm for maximum power point tracking (MPPT) for PV systems operating under partial shaded conditions. Appl. Soft Comput. 32, 38–48, (2015) [CrossRef] [Google Scholar]
  9. H.u. Chao, W. Long, L. Huan, L. Xiong, W. Jenq-Haur. A hybrid global maximum power point tracking method for photovoltaic arrays under partial shading conditions. Optik Int. J. Light Electron Opt., 180, 665–674, (2019) [CrossRef] [Google Scholar]
  10. El-Khozondar, J. Hala El-Khozondar, J. Rifa Matter, Khaled, Suntio, Teuvo. A review study of photovoltaic array maximum power tracking algorithms. Renewables, 3, 3, 1–8, (2016). [CrossRef] [Google Scholar]
  11. Farh, M.H. Hassan Eltamaly, M. Ali Othman, F. Mohd. Hybrid PSO-FLC for dynamic global peak extraction of the partially shaded photovoltaic system. PLoS One 13, 11, (2018) [Google Scholar]
  12. I. Haidar, S. Mekhilef, N.B. Mohamed Shah, T.K. Soon, M. Seyedmahmousian, B. Horan, A. Stojcevski. Performance evaluation of maximum power point tracking approaches and photovoltaic systems. Energies,11, (2018) [Google Scholar]
  13. C. Huang, L. Wang, R.S.C. Yeung, Z. Zhang, H.S.H. Chung, A. Bensoussan. A prediction model-guided jaya algorithm for the PV system maximum power point tracking. IEEE Trans. Sustain. Energy, 9, 1, 45–55, (2018) [CrossRef] [Google Scholar]
  14. S. Ji-Ying, X. Fei, Q. Zi-Jian, Z. Wen, L. Le-Tao, Y. Ting. Improved global maximum power point tracking for photovoltaic system via cuckoo search under partial shaded conditions. J. Power Electron. 16, 1, 287–296, (2016) [CrossRef] [Google Scholar]
  15. L.L. Jiang, D.R. Nayanasiri, Maskell, L. Douglas D.M. Vilathgamuwa. A hybrid maximum power point tracking for partially shaded photovoltaic systems in the tropics. Renew. Energy,76, 53–65, (2015) [CrossRef] [Google Scholar]
  16. Karami, Nabil, Moubayed, Nazih, Outbib, Rachid. General review and classification of different MPPT techniques. Energy Rev.,68, 1, 1–18, (2017) [Google Scholar]
  17. M. Kermadi, E.M. Berkouk. Artificial intelligence-based maximum power point tracking controllers for photovoltaic systems: Comparative study. Renew. Sustain. Energy Rev.,69, 369–386, (2017) [CrossRef] [Google Scholar]
  18. T. Kok Soon, M. Saad, Y. Hong-Tzer, C. Ming-Kai. A differential evolution based MPPT method for photovoltaic modules under partial shading conditions. Int. J. Photoenergy,2014, 1-10, (2014) [Google Scholar]
  19. S. Madeti, S. Singh. Comparative analysis of solar photovoltaic monitoring systems. AIP Conf. Proc.,1859, 1–6, (2017) [Google Scholar]
  20. S. Mirjalili, A. Lewis. The whale optimization algorithm. Adv. Eng. Softw.,95, 51–67, (2016) [CrossRef] [Google Scholar]
  21. S. Mohanty, B. Subudhi, P.K. Ray. A grey wolf-assisted perturb & observe MPPT algorithm for a PV system. IEEE Trans. Energy Convers.,32, 1, 340–347, (2017) [CrossRef] [Google Scholar]
  22. S. Mohanty, B. Subudhi, P.K. Rey. A new MPPT design using gray wolf optimization techniques for photovoltaic systems under partial shading conditions. IEEE Trans. Sustain. Energy.,7, 1, 181–188, (2016) [CrossRef] [Google Scholar]
  23. B. Peng, K. Ho, Y. Liu. A novel and fast MPPT method suitable for both fast changing and partially shaded conditions. IEEE Trans. Ind. Electron.,65, 4, 3240–3251, (2018) [CrossRef] [Google Scholar]
  24. M. Premkumar, K. Karthick, R. Sowmya. A comparative study and analysis on conventional solar PV based DC-DC converters and MPPT techniques. Indones. J. Electr. Eng. Comput. Sci., 11, 3, 831–838, (2018). [Google Scholar]
  25. M. Premkumar, R. Sowmya. Certain study on MPPT algorithms to track the global MPP under partial shading on solar PV module/array. Int. J. Comput. Digit. Syst.,8, 4, 405–416, (2019). [CrossRef] [Google Scholar]
  26. M. Penconi, G. Bianchi, A. Nitti, A. Savoini, C. Carbonera, D. Pasini, R. Po, S. LuzzatiA Contributor Polymer with a Decent Split the difference among Proficiency and Manageability for Natural Sunlight based Cells. Adv. Energy Support. Res.,(2021) [Google Scholar]
  27. I. Etier, A. Al Tarabsheh, N. Kannan. Shunt resistance spatial variations in amorphous silicon solar cells. Microelectron. J., 108, (2021) [Google Scholar]
  28. I.S. Millah, R.K. Subroto, Y.W. Chang, K.L. Lian, B.R. Ke.Examination of Greatest Power Point Following of Various types ofSunlight powered chargers Under Halfway Concealing Circumstances. IEEE Trans. Ind. Appl., 57, 17-25,(2021) [CrossRef] [Google Scholar]
  29. A. Chen, M. Yossef, C. Zhang. Strain effect on the performance of amorphous silicon and perovskite solar cells. Solar Energy, 163, 243-250, (2018). [CrossRef] [Google Scholar]
  30. V M Revathi et al, “A modified invasive weed optimization for MPPT of PV based water pumping system driven by induction motor, IOP: Engineering Research Express, volume 6, number 3, July 2024, 10.1088/2631-8695/ad5cd3. [Google Scholar]
  31. Kandi Bhanu Prakash, Suresh Kakinatla, Sankara Rao Burada and Siva Ganesh Malla, “Hybrid Renewable Energy Sources based Mobile Charging Unit for Public Usage”, 1st International Conference on Power and Energy Systems (ICPES 2023), E3S Web of Conf, Volume 540, June 2024, https://doi.org/10.1051/e3sconf/202454001001. [Google Scholar]
  32. Priyanka Malla, “Novel Control Technique for MPPT of PV Standalone System with TSK Fuzzy controller”, International Journal of New Technologies in Science and Engineering (IJNTSE), Vol. 8, Issue. 8, pp. 1-7, Aug. 2022. [Google Scholar]
  33. Malla, Priyanka, Malla, Siva Ganesh and Calay, Rajnish Kaur. “Voltage control of standalone photovoltaic – electrolyzer- fuel cell-battery energy system” International Journal of Emerging Electric Power Systems, vol. 24, no. 5, 2023, pp. 649-658. https://doi.org/10.1515/ijeeps-2022-0047. [CrossRef] [Google Scholar]
  34. M. Panda, O. Al Zaabi, K. Al Jaafari, P. Kumar, K. Al Hosani and U. R. Muduli, “State-of-Charge Droop Control for Efficient Power Sharing and Transient Response in Microgrids,” 2023 IEEE IAS Global Conference on Emerging Technologies (GlobConET), London, United Kingdom, 2023, pp. 1-5, doi: 10.1109/GlobConET56651.2023.10149905. [Google Scholar]
  35. R. K. Meena, D. V. Bhaskar, O. Al Zaabi, M. Panda, P. Kumar and U. R. Muduli, “Modeling of Two-Stage Photovoltaic Inverter with Grid Connected and Islanding Operation,” 2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT), Male, Maldives, 2023, pp. 1-6, doi: 10.1109/GlobConHT56829.2023.10087517. [Google Scholar]
  36. N. Chaudhary, A. Ranjan, D. V. Bhaskar, M. Panda, A. Kumar and P. Kumar, “Harmonic Reduction Strategies for EV Charging in Power Systems Using Shunt Active Power Filter,” 2023 3rd International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET), Patna, India, 2023, pp. 1-6, doi: 10.1109/ICEFEET59656.2023.10452228. [Google Scholar]
  37. S. K. Baksi, R. K. Behera and U. R. Muduli, “Optimized 9-Level Switched-Capacitor Inverter for Grid-Connected Photovoltaic Systems,” in IEEE Transactions on Industry Applications, vol. 60, no. 2, pp. 3284-3296, March-April 2024, doi: 10.1109/TIA.2023.3332059. [CrossRef] [Google Scholar]
  38. Kandi Bhanu Prakash, “PV-Battery based standalone power supply system for rural applications”, International Journal of New Technologies in Science and Engineering (IJNTSE), Vol. 8, Issue. 12, pp. 9-13, Dec. 2022. [Google Scholar]
  39. A. Saxena et al., “Intelligent Load Forecasting and Renewable Energy Integration for Enhanced Grid Reliability,” in IEEE Transactions on Industry Applications, doi: 10.1109/TIA.2024.3436471. [Google Scholar]
  40. Pragathi, B., Poonia, R.C., Polaiah, B. et al. Evaluation and Analysis of Soft Computing Techniques for Grid Connected Photo Voltaic System to Enhance Power Quality Issues. J. Electr. Eng. Technol. 16, 1833–1840 (2021). https://doi.org/10.1007/s42835-021-00720-w. [Google Scholar]
  41. Pamula Raja Kumari and Polaiah Bojja and B. Pragathi and T Prasanth kumar reddy and P Vijaya Lakshmi, Evaluation and Implementation of Particle Swarm Optimization Maximumpower Point Tracking Technique for Photo Voltaic System, Journal of Physics: Conference Series, Vol 1804, Feb 2021, https://dx.doi.org/10.1088/1742-6596/1804/1/012188. [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.