A crude oil refining is a capital intensive process and releases a huge amount of environmentally unfriendly side‐products. Scheduling of crude oil that determines the optimal unloading of crude from vessels to storages, transfer to blending tanks, and charging to distillation units (CDUs) in a way that minimizes the total operating cost has become the focus of the studies in the last few decades. In this paper, we present a model that extends the literature work of a unit‐specific event‐based model to incorporate desalting as a separate task and allows a desalting tank to feed multiple CDUs. The formulation is based on a state task network (STN) that uses a unit‐specific event‐based time representation. It considers different scenarios like simultaneous or sequential discharging of products and by‐products from a desalting tank and whether a desalting tank feeding to multiple CDUs is allowed simultaneously or not. The proposed model leads a step closure to the reality and enables to know the amount of wash water needed, and the sludge disposed off for treatment in addition to the ordinary crude oil scheduling formulation. The performance of the proposed formulation is demonstrated using four case studies.

中文翻译：

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计划将脱盐作为单独任务进行炼油厂作业

原油精炼是一项资本密集型过程，会释放出大量对环境不利的副产品。确定原油从容器到存储库的最佳卸载，转移到混合罐以及向蒸馏装置（CDU）进料的最佳方式的原油调度已成为过去几十年来研究的重点。在本文中，我们提出了一个模型，该模型扩展了基于单元的基于事件的模型的文献工作，以将脱盐纳入单独的任务中，并允许脱盐罐供入多个CDU。该表述基于状态任务网络（STN），该网络使用特定于单位的基于事件的时间表示。它考虑了不同的情况，例如从脱盐槽同时或顺序排放产品和副产品，以及是否允许同时向多个CDU供入脱盐槽。所提出的模型使步骤一步步逼近了现实，除了常规的原油调度配方外，还能够知道所需的洗涤水量和处理后的污泥。通过四个案例研究证明了所提出配方的性能。