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

    Source: Journal of Solar Energy Engineering:;2020:;volume( 142 ):;issue: 006
    Author:
    Gupta, Anmol
    ,
    Agrawal, Sanjay
    ,
    Pal, Yash
    DOI: 10.1115/1.4046832
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In this paper, a mathematical model of a single-channel photovoltaic thermal (PVT) air collector incorporated with a thermoelectric (TE) module has been presented. The overall electrical energy obtained from the photovoltaic thermal-thermoelectric (PVT-TE) collector is 5.78% higher than the PVT collector. Further, the grasshopper optimization algorithm (GOA) and hybrid grasshopper optimization algorithm with simulated annealing (GOA-SA) have been proposed and implemented to optimize the parameters of opaque PVT-TE collector. Although there are different parameters that influence the performance of PVT-TE system, yet in this study only four parameters, viz., length of the channel (L), width of the channel (b), mass flowrate of air in the channel (mair), and temperature of air at the inlet of channel (Tair,i) are considered for optimization. The simulation result demonstrates that the hybrid GOA-SA algorithm turned out to be an exceptionally effective method for optimal tuning of the parameters of the PVT-TE system. The result explicitly shows that the average value of overall electrical efficiency and exergy gain are 15.27% and 27.0565 W, respectively, when the parameters are optimized by the suggested GOA-SA algorithm which is way ahead with respect to the outcomes obtained with that of the calculated values or using GOA algorithm alone.
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      Performance Evaluation of Hybrid Photovoltaic Thermal Thermoelectric Collector Using Grasshopper Optimization Algorithm With Simulated Annealing

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4273163
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    contributor authorGupta, Anmol
    contributor authorAgrawal, Sanjay
    contributor authorPal, Yash
    date accessioned2022-02-04T14:11:56Z
    date available2022-02-04T14:11:56Z
    date copyright2020/05/05/
    date issued2020
    identifier issn0199-6231
    identifier othersol_142_6_061004.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4273163
    description abstractIn this paper, a mathematical model of a single-channel photovoltaic thermal (PVT) air collector incorporated with a thermoelectric (TE) module has been presented. The overall electrical energy obtained from the photovoltaic thermal-thermoelectric (PVT-TE) collector is 5.78% higher than the PVT collector. Further, the grasshopper optimization algorithm (GOA) and hybrid grasshopper optimization algorithm with simulated annealing (GOA-SA) have been proposed and implemented to optimize the parameters of opaque PVT-TE collector. Although there are different parameters that influence the performance of PVT-TE system, yet in this study only four parameters, viz., length of the channel (L), width of the channel (b), mass flowrate of air in the channel (mair), and temperature of air at the inlet of channel (Tair,i) are considered for optimization. The simulation result demonstrates that the hybrid GOA-SA algorithm turned out to be an exceptionally effective method for optimal tuning of the parameters of the PVT-TE system. The result explicitly shows that the average value of overall electrical efficiency and exergy gain are 15.27% and 27.0565 W, respectively, when the parameters are optimized by the suggested GOA-SA algorithm which is way ahead with respect to the outcomes obtained with that of the calculated values or using GOA algorithm alone.
    publisherThe American Society of Mechanical Engineers (ASME)
    titlePerformance Evaluation of Hybrid Photovoltaic Thermal Thermoelectric Collector Using Grasshopper Optimization Algorithm With Simulated Annealing
    typeJournal Paper
    journal volume142
    journal issue6
    journal titleJournal of Solar Energy Engineering
    identifier doi10.1115/1.4046832
    page61004
    treeJournal of Solar Energy Engineering:;2020:;volume( 142 ):;issue: 006
    contenttypeFulltext
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