A Novel Hybrid Arithmetic-Based Grey Wolf Optimization Method for Tracking the Global Maximum Power Point of Photovoltaic Systems Under Unequal Irradiance Patterns-Reference-Cited by-同舟云学术

A Novel Hybrid Arithmetic-Based Grey Wolf Optimization Method for Tracking the Global Maximum Power Point of Photovoltaic Systems Under Unequal Irradiance Patterns

Published:2023-07-08 Issue:11 Volume:48 Page:15321-15335
ISSN:2193-567X
Container-title:Arabian Journal for Science and Engineering
language:en
Short-container-title:Arab J Sci Eng

Author:

Thota Rajasekar^ORCID,Sinha Nidul

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Link

https://link.springer.com/content/pdf/10.1007/s13369-023-08006-1.pdf

Reference31 articles.

1. Talaat, M.; Farahat, M.A.; Elkholy, M.H.: Renewable power integration: experimental and simulation study to investigate the ability of integrating wave, solar and wind energies. Energy 170, 668–682 (2019). https://doi.org/10.1016/j.energy.2018.12.171

2. Seyedmahmoudian, M.; Horan, B.; Soon, T.K.; Rahmani, R.; Than Oo, A.M.; Mekhilef, S.; Stojcevski, A.: State of the art artificial intelligence-based MPPT techniques for mitigating partial shading effects on PV systems—a review. Renew. Sustain. Energy Rev. 64, 435–455 (2016). https://doi.org/10.1016/j.rser.2016.06.053

3. Bollipo, R.B.; Mikkili, S.; Bonthagorla, P.K.: Hybrid, optimal, intelligent and classical PV MPPT techniques: a review. CSEE J. Power Energy Syst. 7, 9–33 (2021). https://doi.org/10.17775/CSEEJPES.2019.02720

4. Al-Atrash, H.; Batarseh, I.; Rustom, K.: Effect of measurement noise and bias on hill-climbing MPPT algorithms. IEEE Trans. Aerosp. Electron. Syst. 46, 745–760 (2010). https://doi.org/10.1109/TAES.2010.5461654

5. Kjær, S.B.: Evaluation of the hill climbing and the incremental conductance maximum power point trackers for photovoltaic power systems. IEEE Trans. Energy Convers. 27, 922–929 (2012). https://doi.org/10.1109/TEC.2012.2218816

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A novel optimized hybrid machine learning model to enhance the prediction accuracy of hourly building energy consumption;Energy Sources, Part A: Recovery, Utilization, and Environmental Effects;2024-07-15

2. Sand cat arithmetic optimization algorithm for global optimization engineering design problems;Journal of Computational Design and Engineering;2023-10-17