| Title: | OS26-8 Tackling Photovoltaic (PV) Estimation Challenges: An Innovative AOA Variant for Improved Accuracy and Robustness |
|---|---|
| Publication: | ICAROB2024 |
| Volume: | 29 |
| Pages: | 871-876 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2024.OS26-8 |
| Author(s): | Rayan Mohammed Noor Mohammed Bakhit, Abhishek Sharma, Tiong Hoo Lim, Chin Hong Wong, Kim Soon Chong, Li Pan, Sew Sun Tiang, Wei Hong Lim |
| Publication Date: | February 22, 2024 |
| Keywords: | Photovoltaic module/cell, Parameter estimation, Arithmetic optimization algorithm |
| Abstract: | Optimizing photovoltaic (PV) cell/module modeling is key to advancing solar power and achieving net zero carbon goals. Challenges in accurate PV parameter estimation arise from environmental variability, aging, and incomplete manufacturer data. Traditional Arithmetic Optimization Algorithm (AOA) often struggles with premature convergence due to imbalanced exploration and exploitation. This paper presents an enhanced AOA variant, incorporating chaotic maps and oppositional-based learning to better balance the optimization process. Our extensive simulations show that this improved AOA variant significantly enhances accuracy and robustness in PV cell/module parameter estimation compared to the conventional method. |
| PDF File: | https://alife-robotics.co.jp/members2024/icarob/data/html/data/OS/OS26-8.pdf |
| Copyright: | © The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/ |
(c)2008 Copyright The Regents of ALife Robotics Corporation Ltd. All Rights Reserved.