Temperature distribution modeling of PV and cooling water PV/T collectors through thin and thick cooling cross-fined channel box

Gomaa, Mohamed R.; Ahmed, Mohsen; Rezk, Hegazy

doi:10.1016/j.egyr.2021.11.061

Cited by 53 publications

(17 citation statements)

References 19 publications

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“…The PV/T system's thermal efficiency was found as 60% and 68%, at 0.4 and 5.4 L/min mass flow rates, respectively. Gomaa et al 16 analyzed the effectiveness of a PV/T system with a 3 mm‐thin and a 15‐mm‐thick box heat exchanger under varying solar irradiation and cooling fluid flow rates. Yildirim et al 17 proposed the new designed collector for PV/T and found that at 0.014 kg/s flow rate and 15°C inlet temperature of fluid, the thermal and electrical efficiencies of system recorded as 76.13% and 17.19% respectively.…”

Section: Introductionmentioning

confidence: 99%

Machine learning predictive models for optimal design of photovoltaic/thermal collector with nanofluids based geothermal cooling

Jakhar

Paliwal

Kumar

2023

Env Prog and Sustain Energy

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This study aims to estimate the performance of photovoltaic/thermal (PV/T) collector using alumina water‐based nanofluid with geothermal cooling through machine learning (ML) approach. A mathematical model is developed for the first law of thermodynamic analysis of nanofluid in PV/T system integrated with geothermal cooling and is validated with experimental results. Further, a machine learning‐based approach has been employed to simulate the cooling performance of a nanofluid cooling based PV/T system. In the study, Multi‐layer perceptron (MLP) is proposed for estimating the thermal and electrical performance of PV/T system based on design parameters like nanofluid concentration, Reynolds number, and time. The same is then compared with other state‐of‐the‐art machine learning techniques and it is evaluated based on various quality metrics such as mean square error (MSE), root mean square error (RMSE), and R2 test. The designed network is compared with the other ML algorithms available in literature like linear regression (LR), support vector machine (SVM) and decision tree (DT). The proposed MLP network is provided a significant outcome with an average accuracy of 98% and predicted PV panel temperature of 32.1–36.5°C for 0–18 sequences. It was also observed that electrical efficiency of PV/T system improved from 10.51% to 10.66% for 0–18 sequences through MLP predictions.

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Section: Introductionmentioning

confidence: 99%

Machine learning predictive models for optimal design of photovoltaic/thermal collector with nanofluids based geothermal cooling

Jakhar

Paliwal

Kumar

2023

Env Prog and Sustain Energy

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“…[1][2][3][4] The significant advances in PV/T research over the past decade show a substantial improvement in solar energy conversion performance. The utilization of air, 5,6 water, 7,8 nanofluid, [9][10][11] and phase change materials 12,13 for PV module cooling and waste heat recovery enhances the PV/T system efficiency. These heat transfer substances considerably lower the surface temperature of the PV system.…”

Section: Introductionmentioning

confidence: 99%

Performance enhancement study of ag@ SiO ₂ core‐shell nanoplate plasmonic hybrid spectral splitting nanofluid based photovoltaic thermal system in a temperate region

Meraje

Huang

Ujihara

et al. 2022

Intl J of Energy Research

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Summary Nanofluid spectral splitting photovoltaic thermal (PV/T) systems have become immensely common for the utilization of full‐spectrum. The performance enhancement investigation of the plasmonic hybrid nanofluid spectral filtering PV/T system in dynamical modeling and a practical validation was carried out in this study. The Ag@SiO2 core‐shell nanoplate/ethylene glycol‐CoSO4 plasmonic hybrid nanofluid was synthesized to selectively absorb incident natural sunlight. We used H2O2 as a basic shape‐selective oxidant to synthesize the silver nanoplate using a one‐step method. This approach simplifies seed formation and transformation of spherical nanoparticles to different‐sized nanoplates. A practical study of the plasmonic hybrid nanofluid optical filtering PV/T system was conducted outdoors on sunny days to represent the temperate region and evaluate the dynamic modeling and the system's applicability in real situations. It was found that the plasmonic beam splitter serves as an efficient heat transfer medium and maintains the PV module around the ambient temperature. The highest temperature recorded on the typical day of our experiment was 51.62, 54.34, and 57.56°C for the ethylene‐CoSO4 base fluid and nanofluids with concentrations of 18.3 and 28.3 ppm, respectively, and 33.16°C for the PV panel. The highest overall performance of up to 87.6%, 86.4%, and 85.3% was attained by the spectral filtering plasmonic hybrid nanofluid PV/T system using a 27.3 and 18.3 ppm concentration ratio and hybrid base fluid, respectively. The study shows the nanofluid reduces the electricity output but produces higher merit function values than the PV standalone. This shows that the proposed nanofluid is a potential candidate for PV/T systems targeting utilization of full‐spectrum sunlight and enhancing the overall performance.

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“…Solar energy is one of the major sources of renewable energy; it is free and clean. Renewable Energy in many countries produces an important share of the total energy production, Photovoltaic (PV) system is a renewable energy system, which converts the sunlight directly into electricity, the heart of a photovoltaic system is a solid-state device called a solar cell [1][2][3][4][5][6]. In 2019, PV generated 8.2% of gross electricity consumption with an electricity generation of about 46.5 TWh in Germany [7].…”

Section: Introductionmentioning

confidence: 99%

COVID -19 Pandemic Effect on the Solar Irradiance: Case Study Ma`an Development Area

Alsaidat

Gomaa

2022

Engineering World

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Solar Photovoltaic (PV) Panels are converting solar radiation into an electrical form of energy, the performance, and efficiency of PV Panels are affected by several factors including environmental factors represented by air pollutants) typically includes PM10, fine PM2.5, NOx, Sox, and dust), as many studies have found that the efficiency of PV panels cell decrease when the concentration of air pollutant increase, in these study Air pollutant concentration and solar radiation data, were collected during the COVID-19 Pandemic, the result showed that a huge decrease in air pollutant concertation in Jordanian cities and slightly change in the percentage of solar radiation in study area MDA, the recommend to do the study again in an industrial or densely populated area, where pollution rates will be greater, which means a greater impact on the efficiency of solar PV Panels.

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Temperature distribution modeling of PV and cooling water PV/T collectors through thin and thick cooling cross-fined channel box

Cited by 53 publications

References 19 publications

Machine learning predictive models for optimal design of photovoltaic/thermal collector with nanofluids based geothermal cooling

Machine learning predictive models for optimal design of photovoltaic/thermal collector with nanofluids based geothermal cooling

Performance enhancement study of ag@ SiO ₂ core‐shell nanoplate plasmonic hybrid spectral splitting nanofluid based photovoltaic thermal system in a temperate region

COVID -19 Pandemic Effect on the Solar Irradiance: Case Study Ma`an Development Area

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Temperature distribution modeling of PV and cooling water PV/T collectors through thin and thick cooling cross-fined channel box

Cited by 53 publications

References 19 publications

Machine learning predictive models for optimal design of photovoltaic/thermal collector with nanofluids based geothermal cooling

Machine learning predictive models for optimal design of photovoltaic/thermal collector with nanofluids based geothermal cooling

Performance enhancement study of ag@ SiO 2 core‐shell nanoplate plasmonic hybrid spectral splitting nanofluid based photovoltaic thermal system in a temperate region

COVID -19 Pandemic Effect on the Solar Irradiance: Case Study Ma`an Development Area

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Performance enhancement study of ag@ SiO ₂ core‐shell nanoplate plasmonic hybrid spectral splitting nanofluid based photovoltaic thermal system in a temperate region