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A Hybrid Approach Incorporating WSO-HO and the Newton-Raphson Method to Enhancing Photovoltaic Solar Model Parameters Optimisation Cover

A Hybrid Approach Incorporating WSO-HO and the Newton-Raphson Method to Enhancing Photovoltaic Solar Model Parameters Optimisation

Open Access
|Jan 2025

References

  1. Alsattar, H. A., Zaidan, A. A. and Zaidan, B. B. (2020). Novel meta-heuristic bald eagle search optimisation algorithm. Artificial Intelligence Review, 53, pp. 2237–2264. doi: 10.1007/s10462-019-09732-5
  2. Amiri, M. H., Mehrabi Hashjin, N., Montazeri, M., Mirjalili, S. and Khodadadi, N. (2024). Hippopotamus optimization algorithm: A novel nature-inspired optimization algorithm. Scientific Reports, 14, p. 5032. doi: 10.1038/s41598-024-54910-3
  3. Arandian, B., Eslami, M., Khalid, S. A., Khan, B., Sheikh, U. U., Akbari, E. and Mohammed, A. H. (2022). An effective optimization algorithm for parameters identification of photovoltaic models. IEEE Access, 10, pp. 34069–34084. doi: 10.1109/ACCESS.2022.3161467
  4. Ayyarao, T. S. and Kishore, G. I. (2024). Parameter estimation of solar PV models with artificial humming bird optimization algorithm using various objective functions. Soft Computing, 28(4), pp. 3371–3392. doi: 10.1007/s00500-023-08630-x
  5. Ayyarao, T. S. and Kumar, P. P. (2022). Parameter estimation of solar PV models with a new proposed war strategy optimization algorithm. International Journal of Energy Research, 46(6), pp. 7215–7238. doi: 10.1002/er.7629
  6. Bakhshi-Jafarabadi, R., Sadeh, J. and Soheili, A. (2019). Global optimum economic designing of grid-connected photovoltaic systems with multiple inverters using binary linear programming. Solar Energy, 183, pp. 842–850. doi: 10.1016/j.solener.2019.03.019
  7. Bogar, E. (2023). Chaos game optimization-least squares algorithm for photovoltaic parameter estimation. Arabian Journal for Science and Engineering, 48(5), pp. 6321–6340. doi: 10.1007/s13369-022-07364-6
  8. Chen, H., Jiao, S., Heidari, A. A., Wang, M., Chen, X. and Zhao, X. (2019). An opposition-based sine cosine approach with local search for parameter estimation of photovoltaic models. Energy Conversion and Management, 195, pp. 927–942. doi: 10.1016/j.enconman.2019.05.057
  9. Ekinci, S., Izci, D. and Hussien, A. G. (2024). Comparative analysis of the hybrid gazelle-Nelder–Mead algorithm for parameter extraction and optimization of solar photovoltaic systems. IET Renewable Power Generation, 18(6), pp. 959–978. doi: 10.1049/rpg2.12974
  10. El-Khatib, M. F., Sabry, M. N., El-Sebah, I. and Maged, S. A. (2023). Hardware-in-the-loop testing of simple and intelligent MPPT control algorithm for an electric vehicle charging power by photovoltaic system. ISA Transactions, 137, pp. 656–669. doi: 10.1016/j.isatra.2023.01.025
  11. Fan, Y., Wang, P., Heidari, A. A., Chen, H. and Mafarja, M. (2022). Random reselection particle swarm optimization for optimal design of solar photovoltaic modules. Energy, 239, p. 121865. doi: 10.1016/j.energy.2021.121865
  12. Farghally, H., Sweelem, E. A., El-Sebah, I. and Syam, F. (2023). Agricultural grid connected photovoltaic system design and simulation in Egypt by using PVSYST software. WSEAS Transactions on Circuits and Systems, 21, pp. 306–315. doi: 10.37394/23201.2022.21.33
  13. Green, M. A. (1982). Accuracy of analytical expressions for solar cell fill factors. Solar Cells, 7(3), pp. 337–340. doi: 10.1016/0379-6787(82)90057-6
  14. Gu, Z., Xiong, G., Fu, X., Mohamed, A. W., Al-Betar, M. A., Chen, H. and Chen, J. (2023). Extracting accurate parameters of photovoltaic cell models via elite learning adaptive differential evolution. Energy Conversion and Management, 285, p. 116994. doi: 10.1016/j.enconman.2023.116994
  15. Huang, T., Zhang, C., Ouyang, H., Luo, G., Li, S. and Zou, D. (2020). Parameter identification for photovoltaic models using an improved learning search algorithm. IEEE Access, 8, pp. 116292–116309. doi: 10.1109/ACCESS.2020.3003814
  16. Jeridi, A., Moulahi, M. H., Messaoud, R. B. and Zaafouri, A. (2024). Enhancing photovoltaic solar model parameter optimization: WSO-MTBO hybrid approach based on Newton-Raphson method. Przegląd Elektrotechniczny, 11(2024) pp. 133–140, doi: 10.15199/48.2024.11.25
  17. Jordehi, A. R. (2016). Parameter estimation of solar photovoltaic (PV) cells: A review. Renewable and Sustainable Energy Reviews, 61, pp. 354–371. https://doi.org/10.1016/j.rser.2016.03.049
  18. Khattar, N., Sidhu, J. and Singh, J. (2019). Toward energy-efficient cloud omputing: A survey of dynamic power management and heuristics-based optimization techniques. The Journal of Supercomputing, 75, pp. 4750–4810. doi: 10.1007/s11227-019-02764-2
  19. Li, J., Dang, J., Xia, C., Jia, R., Wang, G., Li, P. and Zhang, Y. (2023). Dynamic leader multi-verse optimizer (DLMVO): A new algorithm for parameter identification of solar PV models. Applied Sciences, 13(9), p. 5751. doi: 10.3390/app13095751
  20. Nicaire, N. F., Steve, P. N., Salome, N. E. and Grégroire, A. O. (2021). Parameter estimation of the photovoltaic system using bald eagle search (BES) algorithm. International Journal of Photoenergy, Volume 2021, Article ID 4343203, 20 pages https://doi.org/10.1155/2021/4343203
  21. Qaraad, M., Amjad, S., Hussein, N. K., Badawy, M. and Mirjalili, S. (2023). Photovoltaic parameter estimation using improved moth flame algorithms with local escape operators. Computers and Electrical Engineering, 106, p. 108603. doi: 10.1016/j.compeleceng.2023.108603
  22. Singh, G. K. (2013). Solar power generation by PV (photovoltaic) technology: A review. Energy, 53, pp. 1–13. doi: 10.1016/j.energy.2013.02.057
  23. Villalva, M. G., Gazoli, J. R., and Ruppert Filho, E. (2009). Modeling and circuit-based simulation of photovoltaic arrays. In: 2009 Brazilian Power Electronics Conference (1244–1254), IEEE. 27 September 2009 – 01 October 2009
  24. Xu, B., Heidari, A. A., Kuang, F., Zhang, S., Chen, H. and Cai, Z. (2022). Quantum Nelder-Mead Hunger Games Search for optimizing photovoltaic solar cells. International Journal of Energy Research, 46(9), pp. 12417–12466. doi: 10.1002/er.8011
  25. Yu, S., Chen, Z., Heidari, A. A., Zhou, W., Chen, H. and Xiao, L. (2022). Parameter identification of photovoltaic models using a sine cosine differential gradient based optimizer. IET Renewable Power Generation, 16(8), pp. 1535–1561. doi: 10.1049/rpg2.12451
  26. Yu, X., Hu, Z., Wang, X. and Luo, W. (2023). Ranking teaching–learning-based optimization algorithm to estimate the parameters of solar models. Engineering Applications of Artificial Intelligence, 123, p. 106225. doi: 10.1016/j.engappai.2023.106225
DOI: https://doi.org/10.2478/pead-2025-0003 | Journal eISSN: 2543-4292 | Journal ISSN: 2451-0262
Language: English
Page range: 41 - 59
Submitted on: Aug 30, 2024
Accepted on: Dec 29, 2024
Published on: Jan 27, 2025
Published by: Wroclaw University of Science and Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2025 Ahmed Jeridi, Mohamed Hedi Moulahi, Hechmi Khaterchi, Abderrahmen Zaafouri, published by Wroclaw University of Science and Technology
This work is licensed under the Creative Commons Attribution 4.0 License.