期刊
RENEWABLE ENERGY
卷 36, 期 11, 页码 3146-3153出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.renene.2011.03.018
关键词
Solar thermal electricity; Optimization; Genetic algorithms
资金
- Endesa Generacion
Solar thermal electricity technologies are attractive alternatives to produce electricity by means of a renewable source. One of these technologies is parabolic trough collectors. In Spain, the sale of solar electricity to the national grid is primed. There are three main parameters that affect the behaviour of these plants: area of solar collector field, capacity of thermal storage tanks and power of the auxiliary system. In this paper, a simplified model of the plant is used to optimize the size of its components that produces the maximum yearly profit. The use of traditional methods of optimization is not possible and genetic algorithms have been used. An important feature of the model is that the minimum level of the electricity production of the block of power can be fixed. Once the optimization has been performed, the traditional parameters that characterize the dimension of the plant are analysed (the solar multiple and the capacity factor). For a gross power of 50 MW, the optimum collector area varies between 583,000 m(2) and 749,860 m(2) with a thermal storage between 6.55 h and 13.46 h respectively. The economic benefit is always higher than 19.30 M(sic) per year and the cost of the electricity produced is about 18.5 c(sic)/kWh. (C) 2011 Elsevier Ltd. All rights reserved.
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