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.

这个NSF Goali项目是马萨诸塞大学/阿默斯特大学和Praxair之间的共同努力，旨在开发和实施用于低温空气分离厂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的低阶蒸馏柱模型的构建。 波浪建模方法将应用于用于分离氮，氧和氩气的三重柱植物的问题。 低阶模型将与使用动态模拟工具的Aspen Technology Suite开发的严格低温植物模拟器进行比较。 非线性波模型框架将用于开发专为低温空气分离厂设计的NMPC技术。 将利用Aspen模拟器作为实际低温分离厂的替代物来评估计划的控制策略。 该项目将在德克萨斯州普拉克斯·拉波特（Praxair Laporte）的三重柱NMPC控制器的实施中达到顶峰。晶体生产天然气分离厂生产大量的化学和钢制造业液体和/或气态产品。 工业天然气生产商对国内电力消费估计每年超过7亿美元。 对电力行业的持续放松管制将导致电力成本的更频繁和不可预测的变化。 这将决定天然气分离厂的操作哲学的根本变化。 需要大量的生产率变化和更频繁的启动/关闭，以充分利用时间变化的公用事业成本。 因此，自动过程控制的小改进有可能获得大量经济利益。 代表性工厂的初步经济分析表明，拟议的控制技术有可能在初创企业期间收回损失$ 120,000的产品。 这项研究将为美国的60个低温空气分离厂提供控制系统的原型，并为其他家庭天然气供应商提供非线性控制技术的动力。