New synthesis framework for the optimization of complex distillation systems

Abstract

A new synthesis framework screens and examines complex distillation sequences. Con®entional superstructure de®elopments are replaced in fa®or of a no®el representation that assumes the form of a supertask model. The supertask is based on simple tasks that accommodate for basic sequences. Hybrid tasks account for complex columns and sloppy splits. Discrete instances of simple tasks are combined with hybrid transformations to optimize operating conditions. The optimization problem is formulated as a simple MILP problem that is possible to sol®e to global optimality. The proposed representation can de®elop different noncon®entional and no®el designs featuring fully integrated columns, parallel sequences, and multiple-effect columns. The approach is illustrated with se®eral literature and industrial problems. In all cases solutions are reported in the form of noncon®entional designs that perform as optimal or near-optimal schemes. IntroductionEffective screening of separation systems constitutes a critical stage, as engineers need to review and understand trade-offs ahead of detailed modeling and simulation. In the separation, it is often desired to explore the use of complex rather than simple columns, because the complex units reduce mixing losses, use available vapor and liquid more effec-Ž tively, and improve the separation efficiency Triantafyllou . and Smith, 1992 . Despite its recognized potential in energy savings, complex distillation applications are limited due to their difficult and demanding design and synthesis assignment. Synthesis challenges and operability issues that arise from a more complex dynamic behavior have discouraged wider industry acceptance. A prohibitive number of configurations emerge from different allocations of side-rectifiers, side-strippers, prefractionators, and side-draw columns. Such options are difficult to enumerate and assess. The design alternatives increase rapidly and the trade-offs are impossible Ž . to assess with an exhaustive implicit or explicit enumeration of the options. Although this article does not address dynamCorrespondence concerning this article should be addressed to A. C. Kokossis at this current address: Dept. of Chemical and Process Engineering, University of Surrey, Guildford GU2 5XH, U.K.Current address of P. B. Shah: AEA Technology-Hyprotech, 707-8th Avenue SW, Suite 800, Calgary, Alberta, Canada T2P 3V3.ics, it presents a simultaneous, systematic, and rigorous approach for the automated development of optimal designs. The approach is computationally inexpensive, reliable, and very efficient to implement. It provides the engineer with a selected set of optimal designs on which further attention to dynamics and operability would yield the final design.Previous efforts have focused on the development of shortcut methods that were designed to evaluate fixed configurations and initialize simulation models. Stupin and Lockhart Ž . 1972 developed the equivalent arrangements of simple columns to represent complex configurations. Several other Ž researchers Fi...

Optimal synthesis of thermally coupled distillation sequences using a novel MILP approach

“…Following this approach is remarkable the work by Shah and Kokossis [78,79]. In order to deal with thermal couples they introduce the concept of "supertask".…”

Design and synthesis of separation process based on a hybrid method

“…[9,14] The vapor pressure and relative volatility of the components are calculated The data is presented in Table 4. From the calculating results, the relative volatility of 23-DMB and 2-MP is close to 1.…”

“…For example, Grossmann (1996Grossmann ( , 2003 put up some rigorous algorithms for the separation synthesis, [12,13] but the defects of these approaches are also obvious, cumbersome and overwhelming in terms of computational time and much effort required for algorithms, especially for a complex separation system. Thus, efforts were made by some researches to develop combined methods, for example, Shah (2002) developed a new synthesis framework screens and examined complex distillation sequences based on knowledge and mathematical methods; [14] Zhao (2002) applied Analytical Hierarchy Process (AHP) method to determine the optimal sequence for multicomponent distillation separation. [15] The mathematic algorithmic methods are adopted for modeling; the well-accepted heuristics are used to reduce the size of the search space of the algorithmic methods for simplifying solution, which exploit the advantages of mathematical approach and heuristic or thermodynamic method.…”

“…The heuristic rules and thermodynamic insights were applied for the selection of separation techniques and operations to reduce the complexity and size of synthesis search space. The hybrid method is applied to two illustrative examples which have been carefully selected by taking into account the importance of practical relevance, The first example deals with a light-end refinery mixture; [14] the second example deals with phenol, o-cresol, p-cresol, m-cresol system containing azeotrope.…”

Semantically enabled process synthesis and optimisation

“…Similarly, Shah at al (Shah and Kokossis 2001) attempted to further formulate conceptually rich performance model that makes simultaneous use of engineering insights and MILP optimisation and later to systematically formulate overall framework (Shah and Kokossis 2002). To our knowledge, the first attempt to create a knowledge model of a complex process, a reactor network, was reported by Jacobs (Jacobs et al 1996) who formalised it using production rules.…”