Experimental analysis of CPV/T solar dryer with nano-enhanced PCM and prediction of drying parameters using ANN and SVM algorithms

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Küçük Resim

Tarih

2021

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Pergamon-Elsevier Science Ltd

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

In this paper, a concentrated photovoltaic-thermal solar dryer (CPV/TSD) using nano-enhanced PCM (Al2O3Paraffin wax) is experimentally studied. A comprehensive thermodynamic analysis of the system according to the first and second laws is discussed. Besides, the drying parameters (moisture content and moisture ratio) are predicted using the two machine learning algorithms (ANN and SVM) and compared the prediction success with four evaluation metrics (R2, rRMSE, MBE, and rMAE). The overall thermal energy efficiency and exergy efficiency of the CPV/TSD system are found to be 20% and 8%, respectively. Although solar radiation to the environment has decreased a lot, it has been found that the thermal energy transferred to the nano-enhanced PCM prevents the decrease in greenhouse temperature for the first 100 min. In the system, mushrooms are dried from the initial moisture content of 17.45 g water/g dry matter to the final moisture content of 0.0515 g water/g dry matter. Then the drying rate value for CPV/TSD system is calculated to be 0.436 g matter/g dry matter.min. On the other hand, even if both ANN and SVM algorithms have exhibited very satisfying results, ANN is coming to the fore in the prediction of the drying parameters considering all evaluation metrics together.

Açıklama

Anahtar Kelimeler

Solar Drying, Paraffin wax, Nanoparticle, Thermal energy storage, Nano-enhanced PCM, Prediction algorihtms

Kaynak

Solar Energy

WoS Q Değeri

Q2

Scopus Q Değeri

Q1

Cilt

218

Sayı

Künye