Evaluation of design flexibility in distillation columns using rigorous models

Abstract

A methodology is presented for the evaluation of the flexibility and bottlenecks detection of a given distillation column design, using rigorous simulation models. The flexibility index is calculated as proposed by Swaney and Grossmann (1985), solving a nonlinear programming (NLP) problem in the direction of each vertex in the uncertain space, in which the objective is die maximization of the displacements. The control variables, reflux and product flow rates, are the optimization variables of the NLP. The purity specifications, recovery and maximum equipment capacities are posed as the constraints for feasibility of the NLP. Numerical results will be presented for the case of a debutanizer column. Uncertainties are considered in components feed flow rate, maximum allowed vapor velocity, heat transfer coefficients of condenser and reboiler, and cooling water inlet temperature Great physical insight can be gained from the NLP solutions in the directions of the vertices, detecting bottlenecks and the worst combinations of uncertain parameters KEYWORDS Distillation columns, design, flexibility, bottlenecks.

Design of equipment modules for flexibility

“…i.e. [4][5][6][7][8] more an evaluation than a design method can become impractical and difficult to solve when considering a detailed design including many discrete design parameters…”

“…Evaluation and consideration of flexibility in design approach [10] one at a time analysis transfer of concept to equipment with larger number of design parameters is impractical A widespread approach to evaluate flexibility of a process or an equipment design is based on the flexibility index [4][5][6][7][8]. The focus of these works lies in the quantification and evaluation of flexibility in different dimensions and not on the design.…”

Optimal Cleaning Cycle Scheduling under Uncertain Conditions: A Flexibility Analysis on Heat Exchanger Fouling

“…With the advances in design under uncertainty methodologies and the spread of its applications to thermodynamics [11], unit operations [12][13][14][15][16], reacting systems [17], and other fields of process engineering, the way process scheduling was conceived has started changing even if-differently from process units-a considerably smaller amount of publications about this topic is available in the literature. A pioneering work under this perspective was performed by Balasubramanian and Grossmann that analyzed the scheduling optimization under uncertain processing times with a branch and bound [18] and with a fuzzy programming [19] approach.…”

Exploiting Residue Curve Maps to Assess Thermodynamic Feasibility Boundaries under Uncertain Operating Conditions

“…The inability of a system to withstand operating conditions different from the ones according to which it has been designed indeed can be either due to tight constraints, such as physical laws, or loose constraints, such as available materials or design choices. 2 In the latter case, those limitations can be usually overcome by means of higher investments or at the cost of a lower profitability. On the contrary, in the former cases, it does not exist in any way to bypass the system failure, and a different design solution should be employed.…”

“…However, whether the process results to be unfeasible, it could be very difficult to understand, which is the constraining aspect that prevents the operation to achieve the desired specifications. The inability of a system to withstand operating conditions different from the ones according to which it has been designed indeed can be either due to tight constraints, such as physical laws, or loose constraints, such as available materials or design choices . In the latter case, those limitations can be usually overcome by means of higher investments or at the cost of a lower profitability.…”