Abstract This paper proposes the use of new software called DesalinationPlant to solve the convoluted issue of calculating nominal capacities for an electric-to-water micro-grid comprised by an inexhaustible distributed energy resources; a decentralized storage system, and; a seawater desalination system. For this task, DesalinationPlant will use global stochastic black-box methods to optimize the amount of distributed resources and decentralized batteries coupled to a water desalination system. The final aim of this optimization is to maximize the profits of renewable micro-grid. DesalinationPlant is able to model very complex engineering systems, obtaining a feasible optimum in a limited time due to the small volume of evaluations needed to come to an optimum result. In this article, a complete desalination system associated with a photovoltaic plant, a wind power plant, electrochemical storage and a connection to the electric network was modeled to optimize the sizing of the distributed renewable resources. The optimization produces useful “optimal” values of the objective function, very “expensive” per se, in less than 100 evaluations. Therefore, it can be concluded that the method used, the DYCORS method is an excellent alternative to other black-box optimization methods such as genetic algorithms.

中文翻译：

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基于太阳能光伏和风能的海水淡化微电网中耦合能源的替代优化

摘要 本文提出使用名为 DesalinationPlant 的新软件来解决计算由取之不尽的分布式能源组成的电转水微电网标称容量的复杂问题；一个去中心化的存储系统，以及；海水淡化系统。对于这项任务，DesalinationPlant 将使用全局随机黑盒方法来优化与海水淡化系统耦合的分布式资源和分散电池的数量。这种优化的最终目的是最大化可再生微电网的利润。DesalinationPlant 能够对非常复杂的工程系统进行建模，由于获得最佳结果所需的评估量很小，因此可以在有限的时间内获得可行的优化方案。在本文中，对与光伏电站、风力发电站、电化学存储和电网连接相关的完整海水淡化系统进行建模，以优化分布式可再生资源的规模。在不到 100 次评估中，优化产生了有用的目标函数的“最佳”值，本身非常“昂贵”。因此，可以得出结论，所使用的方法，DYCORS 方法是遗传算法等其他黑盒优化方法的极好替代方法。