Optimization with Genetic Algorithms of PVT System Global Efficiency  

Optimization with Genetic Algorithms of PVT System Global Efficiency

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作  者:Giampietro Fabbri Matteo Greppi Marco Lorenzini 

机构地区:[1]Department of Energy, Nuclear and Environmental Protection, Bologna University, Bologna 40136, Italy [2]Faculty of Engineering, Bologna University, Forli 47100, Italy

出  处:《Journal of Energy and Power Engineering》2012年第7期1035-1041,共7页能源与动力工程(美国大卫英文)

摘  要:PV (photovoltaic) solar panels generally produce electricity in the 6% to 12% efficiency range, the rest is being dissipated in thermal losses. To recover this amount, hybrid photovoltaic thermal systems (PV/T) have been devised. These are devices that simultaneously convert solar energy into electricity and heat. It is thus interesting to study the PV/T system as part of a closed loop single phase water CDU (coolant distribution unit) in laminar forced convection. In particular, the analysis was conducted on the optimal cooling performance of the thermal part, testing polynomial channel profiles of varying order (from zero to fourth) for channels of a real industrial module heat sink, under the following conditions: ideal flux of 1,000 W/m2 on one side, insulation on the opposite side, periodic conditions on the remaining sides, fully developed thermal and velocity profile in laminar flow of water. Through the use of a genetic algorithm, we have optimized the shape of the channel's sidewalls in terms of heat transfer maximization. In terms of Nusselt number, results show that fourth order profiles are the most efficient. When limits to allowable pressure loss and module weight are introduced, these bring generally to a lower efficiency of the system than the unconstrained case.

关 键 词:FINS genetic alghoritms multi objective optimization COOLING PVT systems. 

分 类 号:O414.1[理学—理论物理] O242.23[理学—物理]

 

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