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Automatic load change system of cryogenic air separation process

机译：低温空分过程自动负荷改变系统

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摘要

In this paper, an automatic load change (ALC) system of cryogenic air separation process is developed to automatically and rapidly respond to the changing product demand from customers. In this automatic load change system, a two-layer framework integrated with nonlinear steady-state optimization and nonlinear model predictive control is designed. Nonlinear steady-state optimization based on homoto-py-based backtracking method is performed offline to obtain optimal operating points at various load demands. Nonlinear regression models between optimal operating point and load demand are fitted, which can be easily evaluated online to avoid computational effort and convergence problem. To overcome the pronounced nonlinearities caused by load change, an operating trajectory linear parameter varying (LPV) model is identified to represent the nonlinear dynamic behavior of air separation process. A nonlinear model predictive control (MPC) based on LPV model is designed to drive air separation process rapidly to the optimal operating point of target load demand. Under this framework, material and energy balances of air separation process is actively established during the load change, and load transition time can be shortened. Industrial application results show that oxygen release ratio and unit electric consumption of air separation process are reduced by the implementation of ALC system.
机译：本文开发了一种用于低温空分过程的自动负载变化（ALC）系统，以自动快速地响应客户不断变化的产品需求。在此自动负载变化系统中，设计了一个集成了非线性稳态优化和非线性模型预测控制的两层框架。离线执行基于基于基于均值的回溯方法的非线性稳态优化，以获得在各种负载需求下的最佳工作点。拟合了最佳工作点和负载需求之间的非线性回归模型，可以轻松地在线对其进行评估，以避免计算量和收敛问题。为了克服由负载变化引起的明显的非线性，确定了运行轨迹线性参数变化（LPV）模型来表示空气分离过程的非线性动力学行为。设计了基于LPV模型的非线性模型预测控制（MPC），以将空气分离过程快速驱动到目标负荷需求的最佳工作点。在这种框架下，在负荷变化过程中可以积极建立空分过程的物料和能量平衡，并可以缩短负荷过渡时间。工业应用结果表明，采用ALC系统可以降低空分过程的氧气释放率和单位电耗。

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