GOALI: Low-Order Dynamic Modeling and Nonlinear Model Predictive Control of Cryogenic Gas Separation Plants

GOALI：低温气体分离装置的低阶动态建模和非线性模型预测控制

• 批准号: 0241211
• 负责人: Michael Henson
• 金额: $ 25.17万
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-12-15 至 2005-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0241211&HistoricalAwards=false
• 关键词: GOALI; Low; Order; Dynamic; Modeling

This NSF GOALI project is a joint effort between the University of Massachusetts/Amherst and Praxair aimed at the development and implementation of nonlinear model predictive control (NMPC) technology for cryogenic air separation plants. The planned methodology involves the construction of low-order distillation column models based on nonlinear wave theory. The wave modeling approach will be applied to the problem of triple column plant used to separate nitrogen, oxygen and argon. The low-order models will be compared to a rigorous cryogenic plant simulator developed using the Aspen Technology suite of dynamic simulation tools. The nonlinear wave-modeling framework will be used to develop NMPC technology specifically designed for cryogenic air separation plants. The planned control strategy will be evaluated utilizing the Aspen simulator as a surrogate for an actual cryogenic separation plant. The project will culminate with the implementation of the triple column NMPC controller at the Praxair Laporte, Texas plant site.Cryogenic gas separation plants produce large quantities of liquid and/or gaseous products for the chemical and steel manufacturing industries. Domestic consumption of electricity by industrial gas producers is estimated to be over $700 million per year. Continued deregulation of the electric utility industry will lead to more frequent and unpredictable changes in electricity costs. This will dictate fundamental changes in the operating philosophy of gas separation plants. Large production rate changes and more frequent startups/shutdowns will be required to take full advantage of time-varying utility costs. Consequently, small improvements in automatic process control have the potential for substantial economic benefits. Preliminary economic analysis for a representative plant indicates that the proposed control technology has the potential to recover $120,000/year of products lost during startups. The research will provide Praxair with a control system prototype for the 60 cryogenic air separation plants in the United States and will provide impetus for other domestic gas suppliers to implement nonlinear control technology.

NSF GOALI 项目是马萨诸塞大学/阿默斯特分校和普莱克斯的共同努力，旨在开发和实施用于低温空气分离设备的非线性模型预测控制 (NMPC) 技术。 计划的方法涉及基于非线性波理论构建低阶蒸馏塔模型。 波建模方法将应用于用于分离氮、氧和氩的三塔装置的问题。 低阶模型将与使用 Aspen Technology 动态仿真工具套件开发的严格低温工厂模拟器进​​行比较。 非线性波建模框架将用于开发专为低温空气分离装置设计的 NMPC 技术。 将利用阿斯彭模拟器作为实际低温分离设备的替代品来评估计划的控制策略。 该项目最终将在德克萨斯州普莱克斯拉波尔特工厂实施三柱 NMPC 控制器。低温气体分离工厂为化学和钢铁制造行业生产大量液体和/或气体产品。 工业气体生产商的国内电力消耗每年估计超过 7 亿美元。 电力行业的持续放松管制将导致电力成本发生更频繁且不可预测的变化。 这将决定气体分离工厂的运营理念发生根本性变化。 为了充分利用随时间变化的公用事业成本，需要进行较大的生产率变化和更频繁的启动/关闭。 因此，自动过程控制的微小改进就有可能带来巨大的经济效益。 对代表性工厂的初步经济分析表明，所提议的控制技术有可能每年收回启动期间损失的产品 120,000 美元。 该研究将为普莱克斯提供美国60座低温空分装置的控制系统样机，并将为国内其他气体供应商实施非线性控制技术提供动力。