首页> 外文期刊>International Journal of Solar Energy: Photovoltaics, Heating, Biomass, Wind >The thermal characteristics and economic analysis of a solar pond coupled low temperature multi stage desalination plant Part I: Thermal characteristics
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The thermal characteristics and economic analysis of a solar pond coupled low temperature multi stage desalination plant Part I: Thermal characteristics

机译:太阳池低温多级海水淡化厂的热特性和经济分析第一部分:热特性

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摘要

Salt Gradient Solar Ponds (SGSP) have the potential of providing low grade energy with the advantage of an annual thermal energy storage cycle. The development of Multi-Stage Flash (MSF) distillation plants operating below 100 °C allows SGSP to be considered as the heat source for these systems. In this paper, two schemes of matching the SGSP with the MSF distillation plant are presented. The first scheme is based on the assumption that the solar pond is to be used as the sole heat source for the distillation plant (i. e. all the plant's thermal energy requirements are provided by the solar pond). The second scheme considers a hybrid system (solar + fuel), where a 20,000 m~2 solar pond is linked to an otherwise stand alone, fuel driven desalination plant. Both options are simulated with the same daily product water output of 1000 m~3/day. The thermal simulation of the MSF desalination process was predicted by using a mathematical model based on stage by stage calculations taking into account the variations in fluid properties and flow conditions. The generated simultaneous equations of the mass and energy balances were combined and arranged in a matrix form and then translated into algorithm to predict process variables such as temperature and flash evaporation rates.
机译:盐梯度太阳能池塘(SGSP)具有提供年度热能储存周期优势的潜力,可提供低等级能源。在100°C以下运行的多级闪蒸(MSF)蒸馏设备的开发使SGSP被视为这些系统的热源。本文提出了两种将SGSP与MSF精馏装置相匹配的方案。第一种方案是基于以下假设:太阳能池将用作蒸馏厂的唯一热源(即,该厂的所有热能需求都由太阳能池提供)。第二种方案考虑的是混合系统(太阳能+燃料),其中20,000 m〜2的太阳能水池与原本由燃料驱动的海水淡化厂相连。两种选择均以每天1000 m〜3的相同日产水量进行模拟。 MSF脱盐过程的热模拟是通过使用数学模型进行预测的,该模型基于逐步计算,并考虑了流体特性和流动条件的变化。将生成的质量和能量平衡的联立方程组合并以矩阵形式排列,然后转换为算法以预测过程变量,例如温度和闪蒸速率。

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