基于双层代理模型的原油蒸馏装置优化设计

Ying Xiong, Xuhua Shi, Yongjian Ma, Yifan Chen
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引用次数: 0

摘要

原油蒸馏装置是炼油工业中最重要的分离装置之一。针对CDU进化优化设计中耗时的目标和约束条件,提出了一种双层代理柱模型辅助约束优化设计(Bi-SACOD)。Bi-SACOD的主要组成部分包括双层代理模型构建(Bi-SMC)、双层模型管理(Bi-MM)和粒子群优化(PSO)混合整数约束进化(PSO-MICE)搜索。Bi-SMC实现了代理柱模型的构建和可行域的识别。Bi-MM将代理列模型与严格的CDU模拟相结合来执行模型管理,PSO-MICE实现最佳搜索工作。CDU的优化结果表明,Bi-SACOD优于单层代理柱模型方法,与严格的CDU模型优化方法更加一致,而耗时的严格模型的评估次数显著减少。
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Optimization design of crude oil distillation unit using bi-level surrogate model
Crude Oil Distillation Unit (CDU) is one of the most important separation installations in the petroleum refinery industries. In this work, a Bi-level Surrogate column model Aided Constrained Optimization Design (Bi-SACOD) is proposed for time-consuming objectives and constraints in the evolutionary optimization design of CDUs. The main components of Bi-SACOD include bi-level surrogate model construction (Bi-SMC), bi-level model management (Bi-MM), and particle swarm optimization (PSO) mixed-integer constrained evolutionary (PSO-MICE) search. Bi-SMC implements surrogate column model construction and feasible domain identification. Bi-MM combines surrogate column models with rigorous CDU simulations to perform model management, and PSO-MICE implements optimum search works. The optimization results of the CDUs indicate that Bi-SACOD outperforms the single-level surrogate column model approaches, and are more consistent with the rigorous CDU model optimization approach, whereas the evaluation numbers of the time-consuming rigorous models are significantly reduced.
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