Detection of dry and wet cocoa beans to improve quality using Convolutional Neural Network-based You Only Look Once Architecture

Energy generated from photovoltaic (PV) systems is often wasted, with about 80% converted to heat and only 20% converted to electricity. This indicates the need for further research to improve the energy conversion efficiency in PV systems. This study aims to analyze the cell efficiency and power generation in a photovoltaic-thermal (PVT) system with variations in nano-encapsulated phase change material (NEPCM) concentration and reservoir thickness. The developed PVT configuration includes a photovoltaic cell layer, a thermal paste layer, a reservoir wall, and a channel filled with nanofluid containing NEPCM surrounded by a protective shell. The research method involves simulation using the Finite Element Method to measure system performance regarding energy conversion efficiency, with encapsulated PCM concentration variations at 2%, 10%, and 20%. Additionally, the laminar flow velocity used is 0.5 m/s under steady-state conditions, and the thickness of the PCM material used is 1 mm and 15 mm. The results show that increasing the NEPCM concentration by 5% can improve the electrical and thermal performance of the system by more than 50%. In addition, variations in reservoir thickness also contribute to the overall efficiency. This study concludes that the proposed PVT configuration can improve energy efficiency and optimize thermal management in the system, making it an effective solution for developing renewable energy technologies. Thus, implementing NEPCM in PVT systems can significantly contribute to overall energy efficiency.

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Publication Details

Journal
Jurnal Nasional Teknik Elektro
Published
2025-03-29
DOI
https://doi.org/10.25077/jnte.v14n1.1178.2025
Primary Topic
Spectroscopy and Chemometric Analyses
Type
article
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article

Detection of dry and wet cocoa beans to improve quality using Convolutional Neural Network-based You Only Look Once Architecture

Ramzi Adriman, Roslidar Roslidar, Syahrial Syahrial, Muhammad Khalis Fikri
Jurnal Nasional Teknik Elektro
Spectroscopy and Chemometric Analyses
article

Detection of dry and wet cocoa beans to improve quality using Convolutional Neural Network-based You Only Look Once Architecture

Ramzi Adriman, Roslidar Roslidar, Syahrial Syahrial, Muhammad Khalis Fikri
article en

Abstract

Energy generated from photovoltaic (PV) systems is often wasted, with about 80% converted to heat and only 20% converted to electricity. This indicates the need for further research to improve the energy conversion efficiency in PV systems. This study aims to analyze the cell efficiency and power generation in a photovoltaic-thermal (PVT) system with variations in nano-encapsulated phase change material (NEPCM) concentration and reservoir thickness. The developed PVT configuration includes a photovoltaic cell layer, a thermal paste layer, a reservoir wall, and a channel filled with nanofluid containing NEPCM surrounded by a protective shell. The research method involves simulation using the Finite Element Method to measure system performance regarding energy conversion efficiency, with encapsulated PCM concentration variations at 2%, 10%, and 20%. Additionally, the laminar flow velocity used is 0.5 m/s under steady-state conditions, and the thickness of the PCM material used is 1 mm and 15 mm. The results show that increasing the NEPCM concentration by 5% can improve the electrical and thermal performance of the system by more than 50%. In addition, variations in reservoir thickness also contribute to the overall efficiency. This study concludes that the proposed PVT configuration can improve energy efficiency and optimize thermal management in the system, making it an effective solution for developing renewable energy technologies. Thus, implementing NEPCM in PVT systems can significantly contribute to overall energy efficiency.

Jurnal Nasional Teknik Elektro
Universitas Syiah Kuala (ID)
Openalex Percentile: Top 93%
Spectroscopy and Chemometric Analyses
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Detection of dry and wet cocoa beans to improve quality using Convolutional Neural Network-based You Only Look Once Architecture — Ramzi Adriman, Roslidar Roslidar, et al. · Jurnal Nasional Teknik Elektro (2025) | TGRS Research Map | TGRS