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INTEGRATED OPTIMIZATION OF A SOLAR-POWERED HUMIDIFICATION- DEHUMIDIFICATION DESALINATION SYSTEM FOR SMALL COMMUNITIES

机译:小型社区太阳能加湿除湿除盐系统的综合优化

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Fresh water availability is essential for the economic growth and development, especially in small and semi-isolated communities. In some of these communities fresh water may be scarce, yet brackish water from wells or seawater is often abundantly available. This motivates a need for cost-effective desalination at small scale capacity driven by renewable energy sources. This paper presents an integrated optimization model of a solar powered humidification-dehumidification (HDH) desalination system. The system under investigation is a water-heated system. The design variables include the sizing of solar collectors, storage tank, humidifier and dehumidifier, as well as air circulation flow rate and operating temperature. The objective of the optimization is to minimize the unit cost of the produced fresh water. Thermodynamic performance prediction is done by solving energy and mass balance equations for each of the system components, with consideration to hourly-varying solar irradiance that corresponds to a typical one year cycle. System cost is predicted via first-order estimators. A genetic algorithm is used to obtain the designs optimized for local climate and market. A case study discusses a desalination plant on the Red Sea near the city of Hurgada.
机译:淡水的供应对于经济增长和发展至关重要,特别是在小型和半隔离社区。在这些社区中的某些社区中,淡水可能很稀少,但井或海水中的微咸水通常很丰富。这激发了对由可再生能源驱动的小规模生产的成本有效的淡化的需求。本文提出了太阳能加湿-除湿(HDH)脱盐系统的集成优化模型。研究中的系统是水加热系统。设计变量包括太阳能收集器,储水箱,加湿器和除湿器的尺寸,以及空气循环流量和工作温度。优化的目的是使生产的淡水的单位成本最小化。通过求解每个系统组件的能量和质量平衡方程式来完成热力学性能预测,同时考虑到与典型的一年周期相对应的时变太阳辐照度。系统成本通过一阶估算器进行预测。遗传算法用于获得针对当地气候和市场优化的设计。案例研究讨论了洪加达市附近红海的海水淡化厂。

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