Process Optimization Using Mixed Integer Nonlinear Programming

Abstract

Real-time dynamic optimization of process models in an online model-based process control computing environment. A Mixed Integer Nonlinear Programming (MINLP) solver utilizes switches to activate and deactivate the first principles model of the process unit. This switch implements MINLP behavior by attaching to a first-principles model.

Description

Process Optimization Using Mixed Integer Nonlinear Programming Background technique [0001] Conventional tools used for continuous process optimization are designed to determine operations such as Or the calculation of optimal operating conditions for a continuous process of petrochemical plant operation. When the optimal decision requires the unit to be turned on or off, Traditional tools for continuous optimization are at a disadvantage because they cannot sufficiently retreat or explore from a locally converged state Potential new state. Additionally, traditional tools require workflows where the user builds a case study for each state and manually Explore the optimality of each case study. For example, a small process with only five switchable units would have thirty-two (ie 2 5 ) possible operating states. Thus, as the number of cells increases linearly, the number of possible operating states and by extension does The difficulty of determining the optima...

AI Technical Summary

Problems solved by technology

These traditional systems and methods are rigid and cannot provide an optimal strategy that quickly takes into account changing process parameters (e.g., changing energy costs)

Images