Proactive thermal management of photovoltaic systems using nanofluid cooling and advanced machine learning models

Proactive thermal management of photovoltaic systems using nanofluid cooling and advanced machine learning models

This study aims to advance thermal management strategies for photovoltaic (PV) systems by evaluating the cooling efficiency of TiO2-water nanofluids and developing robust machine learning (ML) models for predicting surface temperature and power output. The primary objective is to enhance PV system p...

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Bibliographic Details
Main Authors: Masalha, Ismail, Alahmer, Ali, Badran, Omar, Al-Khawaldeh, Mustafa Awwad, Masuri, Siti Ujila, Maaitah, Hussein
Format: Article
Language:en
Published: Springer Science and Business Media B.V. 2025
Subjects:
Condensed Matter Physics
Physical and Theoretical Chemistry
Online Access:http://psasir.upm.edu.my/id/eprint/122295/1/122295.pdf
http://psasir.upm.edu.my/id/eprint/122295/
https://link.springer.com/article/10.1007/s10973-025-14746-z?error=cookies_not_supported&code=4355cdb8-2717-4b6e-9753-279ecf33cb49
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Internet

http://psasir.upm.edu.my/id/eprint/122295/1/122295.pdf
http://psasir.upm.edu.my/id/eprint/122295/
https://link.springer.com/article/10.1007/s10973-025-14746-z?error=cookies_not_supported&code=4355cdb8-2717-4b6e-9753-279ecf33cb49

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