Maximum power tracking method for roof solar cells in intelligent buildings based on particle swarm optimisation
Yingjie Wang and
Caihong Chu
International Journal of Global Energy Issues, 2025, vol. 47, issue 3, 283-301
Abstract:
The maximum power tracking of the rooftop solar cells of intelligent buildings cannot be tracked quickly when the effective photovoltaic array is under uniform illumination because of the slow convergence speed. Therefore, a new method of maximum power tracking of the rooftop solar cells of intelligent buildings based on particle swarm optimisation algorithm is proposed. Firstly, the solar cell model is established, and the influence factors of temperature and light intensity are identified as the factors affecting the tracking effect. Then, the particle swarm optimisation algorithm is introduced to determine the initial position of the battery power parameters. Finally, based on the particle swarm optimisation algorithm, the maximum power tracking of solar cells on the roof of intelligent buildings is realised by solving the function repeatedly. The results show that the proposed algorithm has higher tracking accuracy and better dynamic response ability, and the tracking accuracy is improved by 3.7% and the maximum power point can be tracked again in a short time.
Keywords: mathematical model of photovoltaic cells; I-U characteristic equation; guided wave function; particle swarm optimisation; maximum power point tracking. (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=145983 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ids:ijgeni:v:47:y:2025:i:3:p:283-301
Access Statistics for this article
More articles in International Journal of Global Energy Issues from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().