Experimental study and artificial neural network modeling of a pulsating heat pipe PV/T module using a low-efficiency photovoltaic panel

Qing Liang, Chunliu Fang, Xuechao Ma, Yibo Zhang, Xiaojian Xue and Longlong Yan

Energy, 2025, vol. 334, issue C

Abstract: A pulsating heat pipe photovoltaic/thermal (PV/T) module was proposed to enhance the energy utilization of a low-efficiency PV panel. By integrating a pulsating heat pipe with a monocrystalline silicon PV panel containing internal defects, the module enables simultaneous electricity generation and waste heat recovery. Experimental results demonstrate that the daily average overall energy efficiency of the module reaches 44.69–49.07 %. Furthermore, an artificial neural network model for predicting electrical performance and another model for thermal performance were developed. The two models are linked via a bidirectional coupling mechanism. Coupled predictions using these models for a typical day show that the relative error between the predicted and experimental daily overall energy efficiency is 0.92 %.

Keywords: PV/T module; Artificial neural network; Pulsating heat pipe; Photovoltaic panel; Efficiency (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:334:y:2025:i:c:s0360544225034309

DOI: 10.1016/j.energy.2025.137788

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