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    Flow Rate Optimization of a Linear Concentrating Photovoltaic System

    Source: Journal of Solar Energy Engineering:;2013:;volume( 135 ):;issue: 002::page 21009
    Author:
    Kerzmann, Tony
    ,
    Schaefer, Laura
    DOI: 10.1115/1.4023006
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The world is facing an imminent energy supply crisis. In order to sustain and increase our energy supply in an environmentally conscious manner, it is necessary to advance renewable technologies. An area of recent interest is in concentrating solar energy systems that use very high efficiency solar cells. Much of the recent research in this field is oriented toward three dimensional high concentration systems, but this research focused on a two dimensional linear concentrating photovoltaic (LCPV) system combined with an active cooling and waste heat recovery system. The LCPV system serves two major purposes: it produces electricity and the waste heat that is collected can be used for heating purposes. There are three parts to the LCPV simulation. The first part simulates the cell cooling and waste heat recovery system using a model consisting of heat transfer and fluid flow equations. The second part simulates the GaInP/GaAs/Ge multijunction solar cell output so as to calculate the temperaturedependent electricity generation. The third part of the simulation includes a waste heat recovery model which links the LCPV system to a hot water storage system. Coupling the multijunction cell model, waste heat recovery model and hot water storage system model gives an overall integrated system that is useful for system design, optimization, and acts as a stepping stone for future multijunction cell photovoltaic/thermal (PV/T) systems simulation. All of the LCPV system components were coded in Engineering Equation Solver V8.425 (EES) and were used to evaluate a 6.2 kWp LCPV system under actual weather and solar conditions for the Phoenix, AZ, region. This evaluation was focused on obtaining an optimum flowrate, so as to produce the most electrical and heat energy while reducing the amount of parasitic load from the fluid cooling system pump. Under the given conditions, it was found that an optimal cooling fluid flowrate of 4 gal/min (2.52أ—104m3/s) would produce and average of 45.9 kWh of electricity and 15.9 kWh of heat energy under Phoenix conditions from July 10–19, 2005. It was also found that the LCPV system produced an average of $4.59 worth of electrical energy and displaced $0.79 worth of heat energy, while also displacing a global warming potential equivalent of 0.035 tons of CO2 per day. This simulation uses system input parameters that are specific to the current design, but the simulation is capable of modeling the LCPV system under numerous other conditions.
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      Flow Rate Optimization of a Linear Concentrating Photovoltaic System

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    contributor authorKerzmann, Tony
    contributor authorSchaefer, Laura
    date accessioned2017-05-09T01:02:34Z
    date available2017-05-09T01:02:34Z
    date issued2013
    identifier issn0199-6231
    identifier othersol_135_2_021009.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/153143
    description abstractThe world is facing an imminent energy supply crisis. In order to sustain and increase our energy supply in an environmentally conscious manner, it is necessary to advance renewable technologies. An area of recent interest is in concentrating solar energy systems that use very high efficiency solar cells. Much of the recent research in this field is oriented toward three dimensional high concentration systems, but this research focused on a two dimensional linear concentrating photovoltaic (LCPV) system combined with an active cooling and waste heat recovery system. The LCPV system serves two major purposes: it produces electricity and the waste heat that is collected can be used for heating purposes. There are three parts to the LCPV simulation. The first part simulates the cell cooling and waste heat recovery system using a model consisting of heat transfer and fluid flow equations. The second part simulates the GaInP/GaAs/Ge multijunction solar cell output so as to calculate the temperaturedependent electricity generation. The third part of the simulation includes a waste heat recovery model which links the LCPV system to a hot water storage system. Coupling the multijunction cell model, waste heat recovery model and hot water storage system model gives an overall integrated system that is useful for system design, optimization, and acts as a stepping stone for future multijunction cell photovoltaic/thermal (PV/T) systems simulation. All of the LCPV system components were coded in Engineering Equation Solver V8.425 (EES) and were used to evaluate a 6.2 kWp LCPV system under actual weather and solar conditions for the Phoenix, AZ, region. This evaluation was focused on obtaining an optimum flowrate, so as to produce the most electrical and heat energy while reducing the amount of parasitic load from the fluid cooling system pump. Under the given conditions, it was found that an optimal cooling fluid flowrate of 4 gal/min (2.52أ—104m3/s) would produce and average of 45.9 kWh of electricity and 15.9 kWh of heat energy under Phoenix conditions from July 10–19, 2005. It was also found that the LCPV system produced an average of $4.59 worth of electrical energy and displaced $0.79 worth of heat energy, while also displacing a global warming potential equivalent of 0.035 tons of CO2 per day. This simulation uses system input parameters that are specific to the current design, but the simulation is capable of modeling the LCPV system under numerous other conditions.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleFlow Rate Optimization of a Linear Concentrating Photovoltaic System
    typeJournal Paper
    journal volume135
    journal issue2
    journal titleJournal of Solar Energy Engineering
    identifier doi10.1115/1.4023006
    journal fristpage21009
    journal lastpage21009
    identifier eissn1528-8986
    treeJournal of Solar Energy Engineering:;2013:;volume( 135 ):;issue: 002
    contenttypeFulltext
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