Optimization with Genetic Algorithms of PVT System Global Efficiency
Optimization with Genetic Algorithms of PVT System Global Efficiency作者机构：Department of Energy Nuclear and Environmental Protection Bologna University Bologna 40136 Italy Faculty of Engineering Bologna University Forli 47100 Italy
出 版 物：《Journal of Energy and Power Engineering》 (能源与动力工程（美国大卫英文）)
年 卷 期：2012年第6卷第7期
页 面：1035-1041页
学科分类：080701[工学-工程热物理] 07[理学] 08[工学] 0807[工学-动力工程及工程热物理] 070102[理学-计算数学] 0701[理学-数学]
主 题：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
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/m~2 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.
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