Due to a growing population, globally depleting water supplies, as well as the effects of climate change, demands for water are ever increasing. Reverse osmosis desalination could play a key role in generating new water sources since treating saline water for reuse has become possible. An optimization based framework under food-energy-water nexus considerations is developed in this work to tackle water scarcity sustainably for arid and semi-arid regions. With the aid of a surrogate model, a single reverse osmosis stage is depicted, with which varying desalination process designs can be composed, considering different membrane modules, as well as varying input energy and saline water sources. Then, the process was modeled through a superstructure representation that resulted into a mixed-integer nonlinear optimization problem, enabling the optimization of an array of objectives for a given set of input water and energy supply, as well as output water demand restrictions. The developed framework facilitates informed decision making through the fast screening and optimization of desalination plant designs. To illustrate the elaborated framework methodology, a food-energy-water nexus approach is implemented for South-Central Texas in three distinct scenario analyses.

由于人口的增长，全球水供应的枯竭以及气候变化的影响，对水的需求不断增加。反渗透淡化可能在产生新的水源中起关键作用，因为处理盐水以再利用已成为可能。在这项工作中，开发了一种基于食物-能源-水关系的优化框架，以可持续地解决干旱和半干旱地区的水资源短缺问题。借助于替代模型，描绘了单个反渗透阶段，考虑到不同的膜组件以及输入能量和盐水源的不同，可以组成不同的脱盐工艺设计。然后，通过上层结构表示对过程进行建模，从而产生了混合整数非线性优化问题，可以针对一组给定的输入水和能源供应以及输出水需求限制优化一系列目标。通过快速筛选和优化海水淡化厂设计，已开发的框架有助于做出明智的决策。为了说明详细的框架方法，在三个不同的情景分析中，对德克萨斯州中南部实施了食品-能源-水的联系方法。