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Optimization with Genetic Algorithms of PVT System Global Efficiency

Optimization with Genetic Algorithms of PVT System Global Efficiency
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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.
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)
关键词 FINS genetic alghoritms multi objective optimization COOLING PVT systems. PVT系统 遗传算法 优化 Nusselt数 太阳能电池板 太阳能转换 光伏发电 光电系统
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参考文献6

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