Performance Evaluation of Hybrid Photovoltaic Thermal Thermoelectric Collector Using Grasshopper Optimization Algorithm With Simulated Annealing

Gupta, Anmol; Agrawal, Sanjay; Pal, Yash

doi:10.1115/1.4046832

Cited by 7 publications

(4 citation statements)

References 51 publications

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“…In this section, the performance of the proposed simulated model of PV‐TE‐SWC is validated with the results found in recent state‐of‐the‐art studies. The performance in terms of overall electrical gain, overall thermal gain, and overall exergy gain of the proposed PV‐TE‐SWC (case‐I) is analyzed and compared with the results found in a recent study of PV‐TE air collector (case‐II) 24 in the literature. The weather conditions of New Delhi, India have been taken from IMD (Indian Meteorological Department), Pune for the present work which includes the change in ambient temperature (°C) and solar radiation (W/m 2 ) on an hourly basis from 08:00 to 17:00 hour for a typical day in January as portrayed in Figure 5.…”

Section: Resultsmentioning

confidence: 99%

“…For the PV‐TE system, the overall electrical energy and overall electrical efficiency are expressed as 24 :

E_{el} = E_{PV} + E_{TE} = η_{m} I ((), t) β_{sc} A_{m} - P_{pump} + η_{te} U_{te} ((), T_{te, top} - T_{swc}) β_{te} A_{m},

η_{el} = \frac{E_{el}}{I ((), t) A_{m}} = η_{m} β_{sc} + \frac{[η_{te} U_{te} (T_{te, top} - T_{swc}) β_{te}]}{I ((), t)} - \frac{P_{pump}}{I ((), t) A_{m}} .

…”

Section: Electrical and Exergy Analysis Of Opaque Pv‐te‐sw Collectormentioning

confidence: 99%

“…An experimental model of PVT‐TE air collector is proposed by Nazri et al, 23 and the improvement potential and exergy are analyzed based on different energy balance equations of the collector. Gupta et al 24 found that the outcomes of the PVT‐TE air‐based system are improved by optimizing the different design parameters of the collector. The hybrid PVT‐TE collector is examined in several studies in the literature, and in most of them, an air channel is attached with the PV to extract the heat and create a large temperature gradient across TE terminals.…”

Section: Introductionmentioning

confidence: 99%

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Performance analysis of the photovoltaic‐thermoelectric system combined with serpentine type water collector

2021

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Summary In this work, performance analysis of the photovoltaic‐thermoelectric with serpentine water collector (PV‐TE‐SWC) has been carried out. For extracting the heat from the back surface of the combined PV‐TE system and to maintain a temperature gradient, a serpentine‐type tube and sheet water collector is proposed. The electrical efficiency of the designed PV‐TE‐SWC is compared with the experimental and theoretical results on a similar type of collector from the literature to validate the proposed simulated model. After that, the performance in terms of annual useful thermal energy, annual overall electrical energy, annual useful overall thermal energy, annual thermal exergy, and annual overall exergy of the PV‐TE‐SWC (case‐I) have been carried out and compared with the outcomes of a recent state‐of‐art study on PV‐TE air collector (case‐II). The average improvement in hourly overall electrical efficiency and hourly exergy gain of case‐I have been found by 5.72% and 31.34%, respectively, concerning case‐II. The study shows that the annual performance parameters, that is, overall electrical energy, overall thermal energy, and overall exergy have been observed considerably higher for case‐I by 8.4%, 14.8%, and 41.7%, respectively concerning case‐II. Further, environmental cost analysis based on the price of carbon dioxide emission has also been computed based on annual overall thermal energy and overall exergy generated from the collector.

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Section: Resultsmentioning

confidence: 99%

“…For the PV‐TE system, the overall electrical energy and overall electrical efficiency are expressed as 24 :

E_{el} = E_{PV} + E_{TE} = η_{m} I ((), t) β_{sc} A_{m} - P_{pump} + η_{te} U_{te} ((), T_{te, top} - T_{swc}) β_{te} A_{m},

η_{el} = \frac{E_{el}}{I ((), t) A_{m}} = η_{m} β_{sc} + \frac{[η_{te} U_{te} (T_{te, top} - T_{swc}) β_{te}]}{I ((), t)} - \frac{P_{pump}}{I ((), t) A_{m}} .

…”

Section: Electrical and Exergy Analysis Of Opaque Pv‐te‐sw Collectormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Performance analysis of the photovoltaic‐thermoelectric system combined with serpentine type water collector

2021

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“…These drying system control and manage the drying cabin temperature, as well as other affecting ambient parameters (room temperature, relative humidity, air speed). Adequate dehydration helps in preserving flavor, texture as well as quality assessment in term of color index of dried product [1], [2], [3].…”

Section: Introductionmentioning

confidence: 99%

Application of ANN and prediction of drying behavior of mushroom drying in side hybrid greenhouse solar dryer: An experimental validation

Kushwah

Gaur

Kumar

et al. 2022

Journal of Thermal Engineering

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The newly developed Heat Exchanger Evacuated Tube Assisted Drying System (HE-ETADS) is fabricated in roof of campus of MITS, Gwalior, India. Heat transfer analysis of developed drying system is carried out by drying mushroom inside it. The heat transfer coefficient plays a significant role in drying method. The study emphasizes on determining the convective as well as evaporative heat transfer coefficients (CHTC & EHTC) and the determination of best drying rate model fit for mushroom drying inside novel drying system. The artificial neural network is developed for predicting the CHTC & EHTC. Value of CHTC & EHTC varies from 2.10 to 3.43 and 25.68 to 49.85 W/m 2 °C respectively. The developed ANN model helps in predicting the heat transfer coefficient once trained using input factors like solar radiation, relative humidity, environmental temperature and time. The value of R 2 for the developed ANN model is 0.99, which shows that model predicts the value very close to the calculated value of heat transfer coefficients. Drying kinetics of mushroom is tried to fit in nine drying rate models. The Midili-Kucuk model shows the better fit among the other models.

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Size Optimization of Grid-Tied Hybrid Energy System by Employing Forecasted Meteorological Data

Anand,

Sharma,

Rizwan

2024

MAPAN

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Performance Evaluation of Hybrid Photovoltaic Thermal Thermoelectric Collector Using Grasshopper Optimization Algorithm With Simulated Annealing

Cited by 7 publications

References 51 publications

Performance analysis of the photovoltaic‐thermoelectric system combined with serpentine type water collector

Performance analysis of the photovoltaic‐thermoelectric system combined with serpentine type water collector

Application of ANN and prediction of drying behavior of mushroom drying in side hybrid greenhouse solar dryer: An experimental validation

Size Optimization of Grid-Tied Hybrid Energy System by Employing Forecasted Meteorological Data

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