Bilevel and parallel programing‐based operability approaches for process intensification and modularity

Abstract

Process operability emerged in the last decades as a powerful tool for the design and control of chemical processes. Recent efforts in operability have been focused on the calculation of the desired input set for process design and intensification of natural gas utilization applications described by nonlinear models. However, there is still a gap in terms of problem dimensionality that nonlinear operability methods can handle. To fill this gap, in this article, the incorporation of bilevel and parallel programing approaches into classical process operability concepts is discussed. Results on the implementation of the proposed method show a reduction in computational time up to two orders of magnitude, when compared to the original results without parallelization. These results could be extrapolated for use in a supercomputer as presented in the computational time analysis performed. In terms of intensification, the proposed approach can produce a natural gas combined cycle plant modular design with a dramatic reduction in size, from the original 400 to 0.11 MW, while still keeping the high net plant efficiency. This approach thus provides a computationally efficient framework for process intensification of high-dimensional nonlinear energy systems toward modularity. The proposed approach also enables the verification of a modular design and conditions that can be obtained according to economic and physical constraints associated with a specific natural gas well production.

Dynamic and Statistical Operability of an Experimental Batch Process

“…Operability concepts enable the understanding of how a process can reach desired specifications when subjected to input conditions and limited by design constraints, while considering expected disturbances. In the process operability framework, a generic process model is defined as shown in Figure 1, in which inputs, u ∈ R m , are manipulated inside their available limits, and along with disturbances, d ∈ R q , stimulate the model (M) to generate the outputs, y ∈ R n [3,15].…”

“…The process model (M) can be defined by the first principles or process simulators (e.g., in Aspen Plus, DYNSIM, AVEVA Process Simulation, etc.) to reproduce a real unit and obtain the relationships between input and output spaces [3]. The following sets are essential for the operability analysis: a.…”

“…The inputs for the analysis correspond to the process design and operational limitations, environmental constraints, as well as a group of external disturbances. The outputs cover production targets, quality specifications, business benchmarks, and safetycritical conditions [3].…”

Modeling, Simulation, and Operability Analysis of a Nonisothermal, Countercurrent, Polymer Membrane Reactor

“…This method provides a reliable way of simulating a countercurrent, nonisothermal, and bidirectional-permeation membrane reactor model. Second, with the use of this model, operability analysis [3,4] is performed for a polymer membrane reactor for the first time. The operability concept is used to study the relationship between unit performance and operational decisions.…”

“…Third, the operability analyses are also employed to drive future membrane reactor design decisions. Others have used operability analysis previously to improve membrane reactor design [3][4][5][6], but this proposed approach differs in a key way. Prior work in operability either looked at how design changes could be used to improve a nominal operating point or what the optimal nominal point of a given design would be.…”