Version 1
: Received: 12 July 2024 / Approved: 12 July 2024 / Online: 15 July 2024 (02:59:21 CEST)
How to cite:
Liu, T.; Liu, S.; Yu, H.; Wu, Z.; Tong, J.; Yuan, Q. Photovoltaic Power Generation Systems MPPT Controller Optimization Using IWOA and P&O: A Hybrid Approach under Various Operating Conditions. Preprints2024, 2024071097. https://doi.org/10.20944/preprints202407.1097.v1
Liu, T.; Liu, S.; Yu, H.; Wu, Z.; Tong, J.; Yuan, Q. Photovoltaic Power Generation Systems MPPT Controller Optimization Using IWOA and P&O: A Hybrid Approach under Various Operating Conditions. Preprints 2024, 2024071097. https://doi.org/10.20944/preprints202407.1097.v1
Liu, T.; Liu, S.; Yu, H.; Wu, Z.; Tong, J.; Yuan, Q. Photovoltaic Power Generation Systems MPPT Controller Optimization Using IWOA and P&O: A Hybrid Approach under Various Operating Conditions. Preprints2024, 2024071097. https://doi.org/10.20944/preprints202407.1097.v1
APA Style
Liu, T., Liu, S., Yu, H., Wu, Z., Tong, J., & Yuan, Q. (2024). Photovoltaic Power Generation Systems MPPT Controller Optimization Using IWOA and P&O: A Hybrid Approach under Various Operating Conditions. Preprints. https://doi.org/10.20944/preprints202407.1097.v1
Chicago/Turabian Style
Liu, T., Jiaqi Tong and Qingyun Yuan. 2024 "Photovoltaic Power Generation Systems MPPT Controller Optimization Using IWOA and P&O: A Hybrid Approach under Various Operating Conditions" Preprints. https://doi.org/10.20944/preprints202407.1097.v1
Abstract
This paper proposes a novel approach called Multi-strategy Improved Chaotic Whale fused with Perturbation Observation method (IWOA-PO) for Maximum Power Point Tracking (MPPT) con-trol, to address the challenge of low efficiency in photovoltaic (PV) power generation under local shadows, according to the features of whale optimization algorithm (WOA) and perturbation observation (P&O) method. In the early stage of control algorithm, IWOA is used for global search to quickly locate the position of the Maximum Power Point (MPP). In the later stage of control algorithm, P&O is used for fine-grained local search to quickly, accurately and low oscillation track the position of the global maximum power point (GMPP). In order to verify the correctness, the tracking performance of IWOA-PO is comprehensively compared with WOA-PO、WOA、PSO under four conditions including uniform illumination, static partial shade, dynamic irradiance mutation and sudden changes in temperature and irradiance. In the above four conditions, the IWOA-PO algorithm has faster convergence and less power oscillations compared to the re-maining three algorithms, indicating that the IWOA-PO algorithm is effective. Finally, a physical verification experiment process is built to verify the correctness and effectiveness of the algorithm proposed in this paper.
Keywords
photovoltaic power generation; MPPT control; intelligent algorithm; improved whale optimization algorithm; mixed control strategy
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
