A novel disjunctive model for the simultaneous optimization and heat integration

This paper introduces a new disjunctive formulation for the simultaneous optimization and heat integration of systems with variable inlet and outlet temperatures in process streams as well as the possibility of selecting and using different utilities. The starting point is the original compact formulation of the Pinch Location Method, however, instead of approximating the “maximum” operator with smooth, but non-convex functions, these operators are modeled by means of a disjunction. The new formulation has shown to have equal or lower relaxation gap than the best alternative reformulation, thus reducing computational time and numerical problems related to non-convex approximations.The authors gratefully acknowledge the financial support by the Ministry of Economy and Competitiveness from Spain, under the projects CTQ2012-37039-C02-02, CTQ2016-77968-C3-2-P, and Call 2013 National Sub-Program for Training, Grants for pre-doctoral contracts for doctoral training (BES-2013-064791)

Disjunctive model for the simultaneous optimization and heat integration with unclassified streams and area estimation

In this paper, we propose a disjunctive formulation for the simultaneous chemical process optimization and heat integration with unclassified process streams –streams that cannot be classified a priori as hot or cold streams and whose final classification depend on the process operating conditions–, variable inlet and outlet temperatures, variable flow rates, isothermal process streams, and the possibility of using different utilities. The paper also presents an extension to allow area estimation assuming vertical heat transfer. The model takes advantage of the disjunctive formulation of the ‘max’ operator to explicitly determine all the ‘kink’ points on the hot and cold balanced composite curves and uses an implicit ordering for determining adjacent points in the balanced composite curves for area estimation. The numerical performance of the proposed approach is illustrated with four case studies. Results show that the novel disjunctive model of the pinch location method has excellent numerical performance, even in large-scale models.The authors gratefully acknowledge the financial support by the Ministry of Economy, Industry, and Competitiveness of Spain (CTQ2016-77968-C3-02-P, AEI/FEDER, UE), and Call 2013 National Sub-Program for Training, Grants for pre-doctoral contracts for doctoral training (BES-2013-064791)

Optimization of Triple-Pressure Combined-Cycle Power Plants by Generalized Disjunctive Programming and Extrinsic Functions

A new mathematical framework for optimal synthesis, design, and operation of triple-pressure steam-reheat combined-cycle power plants (CCPP) is presented. A superstructure-based representation of the process, which embeds a large number of candidate configurations, is first proposed. Then, a generalized disjunctive programming (GDP) mathematical model is derived from it. Series, parallel, and combined series-parallel arrangements of heat exchangers are simultaneously embedded. Extrinsic functions executed outside GAMS from dynamic-link libraries (DLL) are used to estimate the thermodynamic properties of the working fluids. As a main result, improved process configurations with respect to two reported reference cases were found. The total heat transfer areas calculated in this work are by around 15% and 26% lower than those corresponding to the reference cases.This paper contributes to the literature in two ways: (i) with a disjunctive optimization model of natural gas CCPP and the corresponding solution strategy, and (ii) with improved HRSG configurations.Fil: Manassaldi, Juan Ignacio. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; ArgentinaFil: Mussati, Miguel Ceferino. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Scenna, Nicolas Jose. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; ArgentinaFil: Mussati, Sergio Fabian. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentin

Logic hybrid simulation-optimization algorithm for distillation design

In this paper, we propose a novel algorithm for the rigorous design of distillation columns that integrates a process simulator in a generalized disjunctive programming formulation. The optimal distillation column, or column sequence, is obtained by selecting, for each column section, among a set of column sections with different number of theoretical trays. The selection of thermodynamic models, properties estimation etc., are all in the simulation environment. All the numerical issues related to the convergence of distillation columns (or column sections) are also maintained in the simulation environment. The model is formulated as a Generalized Disjunctive Programming (GDP) problem and solved using the logic based outer approximation algorithm without MINLP reformulation. Some examples involving from a single column to thermally coupled sequence or extractive distillation shows the performance of the new algorithm.Spanish Ministry of Science and Innovation (CTQ2012-37039-C02-02)

Integration of modular process simulators under the Generalized Disjunctive Programming framework for the structural flowsheet optimization

The optimization of chemical processes where the flowsheet topology is not kept fixed is a challenging discrete-continuous optimization problem. Usually, this task has been performed through equation based models. This approach presents several problems, as tedious and complicated component properties estimation or the handling of huge problems (with thousands of equations and variables). We propose a GDP approach as an alternative to the MINLP models coupled with a flowsheet program. The novelty of this approach relies on using a commercial modular process simulator where the superstructure is drawn directly on the graphical use interface of the simulator. This methodology takes advantage of modular process simulators (specially tailored numerical methods, reliability, and robustness) and the flexibility of the GDP formulation for the modeling and solution. The optimization tool proposed is successfully applied to the synthesis of a methanol plant where different alternatives are available for the streams, equipment and process conditions.Spanish Ministry of Science and Innovation (CTQ2012-37039-C02-02)

Hybrid simulation-equation based synthesis of chemical processes

A challenging problem in the synthesis and design of chemical processes consists of dealing with hybrid models involving process simulators and explicit constraints. Some unit operations in modular process simulators are slightly noisy or require large CPU times to converge. In this work, this problem is addressed by combining process simulators and surrogate models. We have replaced some unit operations, which cannot be used directly with a gradient-based optimization, by surrogate models based on Kriging interpolation. To increase the robustness of the resulting optimization model, we perform a degree of freedom analysis and aggregate (or disaggregate) parts of the model to reduce the number of independent variables of the Kriging surrogate models (KSMs). Thus, the final model is composed of KSMs, unit operations (maintained in the process simulator) and also explicit equations. The optimization of the well-known vinyl chloride monomer (VCM) production process is performed to test the proposed approach. The effect of the heat integration is also studied. In addition, the economic feasibility of the optimized process is calculated assuming uncertainty in raw material and product prices.The authors gratefully acknowledge the financial support by the Ministry of Economy and Competitiveness from Spain, under the project CTQ2016-77968-C3-02-P (AEI/FEDER, UE), and Call 2013 National Sub-Program for Training, Grants for pre-doctoral contracts for doctoral training (BES-2013-064791)

Synthesis and design of integrated reaction-separation systems with complex configurations and rigorous models

Chemical engineering, and specially process design, synthesis and intensification, are well positioned to support both society and industry in overcoming present global challenges of environment degradation, energy supply, water scarcity and food supply. These challenges have been translated into industrial problems that involve the design of chemical processes with decreased water and energy consumption, and improved efficiencies. In this context the present study focuses on the simultaneous synthesis and design of reaction-separation systems including complex configuration distillation columns and using rigorous models. The study is considered a further step in this research area, as previous works have usually focused on the synthesis of sub-networks and have used shortcut models. Additionally, among complex configuration, thermally coupled distillation columns are reported to present significant savings in terms of the total annualised cost of the system. Among the available approaches to synthesis and design, a superstructure optimisation approach is used. The procedure involves the construction of a superstructure that includes a reaction superstructure, taken from Ma et al. (Ma et al. 2019) and a separation superstructure, proposed by Sargent and Gaminibandara (Sargent and K. Gaminibandara 1976). The modelling is performed using generalised disjunctive programming (GDP) to produce a logic-based model. This model is then reformulated into a mixed-integer nonlinear programming (MINLP) optimisation problem, where the objective is to minimise the total annualised cost of the process. For the reformulation convex hull and bypass efficiency methods are used. A modified version of the solving strategy presented by Ma et al. (Ma et al. 2019) is used, which involves using the solver SBB in General Algebraic Modelling System (GAMS). The proposed framework is applied to a case study previously addressed by Zhang et al. (Zhang et al. 2018) and Ma et al. (Ma et al. 2019). Economic models and assumptions made in those studies are maintained in order to evaluate the benefits of including complex configuration columns in the design possibilities. Results present a flowsheet with one PFR reactor and complex configuration distillation columns that are partially thermally coupled. The total annualised cost of the process is 5.85x105 $/yr, which is 6.3% and 4.7% less than the value achieved by Zhang et al. (Zhang et al. 2018)and Ma et al., respectively. Results show that it is both possible and beneficial to consider complex configuration distillation columns, including thermally coupled ones, in the simultaneous synthesis and design of reaction-separation systems using rigorous models.Chevening AwardsAgencia Nacional de Investigación e Innovació