Rigorous design of distillation columns using surrogate models based on Kriging interpolation

The economic design of a distillation column or distillation sequences is a challenging problem that has been addressed by superstructure approaches. However, these methods have not been widely used because they lead to mixed-integer nonlinear programs that are hard to solve, and require complex initialization procedures. In this article, we propose to address this challenging problem by substituting the distillation columns by Kriging-based surrogate models generated via state of the art distillation models. We study different columns with increasing difficulty, and show that it is possible to get accurate Kriging-based surrogate models. The optimization strategy ensures that convergence to a local optimum is guaranteed for numerical noise-free models. For distillation columns (slightly noisy systems), Karush–Kuhn–Tucker optimality conditions cannot be tested directly on the actual model, but still we can guarantee a local minimum in a trust region of the surrogate model that contains the actual local minimum.The authors gratefully acknowledge the financial support of the Ministry of Economy and Competitiveness of Spain, under the project 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)

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)

Environmental and Economic Water Management in Shale Gas Extraction

This paper introduces a comprehensive study of the Life Cycle Impact Assessment (LCIA) of water management in shale gas exploitation. First, we present a comprehensive study of wastewater treatment in the shale gas extraction, including the most common technologies for the pretreatment and three different desalination technologies of recent interest: Single and Multiple-Effect Evaporation with Mechanical Vapor Recompression and Membrane Distillation. The analysis has been carried out through a generic Life Cycle Assessment (LCA) and the ReCiPe metric (at midpoint and endpoint levels), considering a wide range of environmental impacts. The results show that among these technologies Multiple-Effect Evaporation with Mechanical Vapor Recompression (MEE-MVR) is the most suitable technology for the wastewater treatment in shale gas extraction, taking into account its reduced environmental impact, the high water recovery compared to other alternatives as well as the lower cost of this technology. We also use a comprehensive water management model that includes previous results that takes the form of a new Mixed-Integer Linear Programming (MILP) bi-criterion optimization model to address the profit maximization and the minimization Life Cycle Impact Assessment (LCIA), based on its results we discuss the main tradeoffs between optimal operation from the economic and environmental points of view.This project has received funding from the Spanish «Ministerio de Economía, Industria y Competitividad» under the projects CTQ2016-77968-C3-1-P and CTQ2016-77968-C3-2-P (FEDER, UE)

Economic and environmental strategic water management in the shale gas industry: Application of cooperative game theory

In this work, a mixed‐integer linear programming (MILP) model is developed to address optimal shale gas‐water management strategies among shale gas companies that operate relatively close. The objective is to compute a distribution of water‐related costs and profit among shale companies to achieve a stable agreement on cooperation among them that allows increasing total benefits and reducing total costs and environmental impacts. We apply different solution methods based on cooperative game theory: The Core, the Dual Core, the Shapley value, and the minmax Core. We solved different case studies including a large problem involving four companies and 207 wells. In this example, individual cost distribution (storage cost, freshwater withdrawal cost, transportation cost, and treatment cost) assigned to each player is included. The results show that companies that adopt cooperation strategies improve their profits and enhance the sustainability of their operations through the increase in recycled water.The authors gratefully acknowledge the financial support by the Ministry of Economy, Industry, and Competitiveness from Spain, under the projects CTQ2016-77968-C3-1-P and CTQ2016-77968-C3-2-P (AEI/FEDER, UE)

Rigorous Design of Chemical Processes: Surrogate Models and Sustainable Integration

El desarrollo de procesos químicos eficientes, tanto desde un punto de vista económico como desde un punto de vista ambiental, es uno de los objetivos principales de la Ingeniería Química. Para conseguir este propósito, durante los últimos años, se están empleando herramientas avanzadas para el diseño, simulación, optimización y síntesis de procesos químicos, las cuales permiten obtener procesos más eficientes y con el menor impacto ambiental posible. Uno de los aspectos más importantes a tener en cuenta para diseñar procesos más eficientes es la disminución del consumo energético. El consumo energético del sector industrial a nivel global representa aproximadamente el 22.2 % del consumo energético total, y dentro de este sector, la industria química representa alrededor del 27 %. Por lo tanto, el consumo energético de la industria química a nivel global constituye aproximadamente el 6 % de toda la energía consumida en el mundo. Además, teniendo en cuenta que la mayor parte de la energía consumida es generada principalmente a partir de combustibles fósiles, cualquier mejora de los procesos químicos que reduzca el consumo energético supondrá una reducción del impacto ambiental. El trabajo recopilado en esta Tesis Doctoral se ha llevado a cabo dentro del grupo de investigación COnCEPT, perteneciente al Instituto Universitario de Ingeniería de los Procesos Químicos de la Universidad de Alicante, durante los años 2014 y 2017. El objetivo principal de la presente Tesis Doctoral se centra en el desarrollo de herramientas y modelos de simulación y optimización de procesos químicos con el fin de mejorar la eficiencia energética de éstos, lo que conlleva a la disminución del impacto ambiental de los procesos. Más concretamente, esta Tesis Doctoral se compone de dos estudios principales, que son los objetivos concretos que se pretenden conseguir: - Estudio y evaluación de los modelos surrogados para la mejora en la optimización basada en simuladores de procesos químicos. - Desarrollo de nuevos modelos para la optimización de procesos químicos y la integración de energía simultánea, para redes de intercambiadores de calor

Rigorous Design of Chemical Processes: Surrogate Models and Sustainable Integration

El desarrollo de procesos químicos eficientes, tanto desde un punto de vista económico como desde un punto de vista ambiental, es uno de los objetivos principales de la Ingeniería Química. Para conseguir este propósito, durante los últimos años, se están empleando herramientas avanzadas para el diseño, simulación, optimización y síntesis de procesos químicos, las cuales permiten obtener procesos más eficientes y con el menor impacto ambiental posible. Uno de los aspectos más importantes a tener en cuenta para diseñar procesos más eficientes es la disminución del consumo energético. El consumo energético del sector industrial a nivel global representa aproximadamente el 22.2 % del consumo energético total, y dentro de este sector, la industria química representa alrededor del 27 %. Por lo tanto, el consumo energético de la industria química a nivel global constituye aproximadamente el 6 % de toda la energía consumida en el mundo. Además, teniendo en cuenta que la mayor parte de la energía consumida es generada principalmente a partir de combustibles fósiles, cualquier mejora de los procesos químicos que reduzca el consumo energético supondrá una reducción del impacto ambiental. El trabajo recopilado en esta Tesis Doctoral se ha llevado a cabo dentro del grupo de investigación COnCEPT, perteneciente al Instituto Universitario de Ingeniería de los Procesos Químicos de la Universidad de Alicante, durante los años 2014 y 2017. El objetivo principal de la presente Tesis Doctoral se centra en el desarrollo de herramientas y modelos de simulación y optimización de procesos químicos con el fin de mejorar la eficiencia energética de éstos, lo que conlleva a la disminución del impacto ambiental de los procesos. Más concretamente, esta Tesis Doctoral se compone de dos estudios principales, que son los objetivos concretos que se pretenden conseguir: - Estudio y evaluación de los modelos surrogados para la mejora en la optimización basada en simuladores de procesos químicos. - Desarrollo de nuevos modelos para la optimización de procesos químicos y la integración de energía simultánea, para redes de intercambiadores de calor

A New Disjunctive Formulation for the Simultaneous Optimization and Heat Integration with Cold/Hot and Unclassified Streams

In this work, we present a new disjunctive model for the simultaneous optimization and heat integration of systems with variable input and output process stream temperatures. We also extend the study in order to include the possibility of selecting and using different utilities, as well as the possibility of including unclassified streams. The study is based on the original compact formulation of the Pinch Location Method, where the ‘max’ operators have been modeled by means of a disjunction. This new model is very competitive, solving large problems in a reduced CPU time.The authors wish to acknowledge the financial support by the Ministry of Economy, Industry, and Competitiveness from Spain, under the project CTQ2016-77968-C3-2-P

Optimal synthesis of work and heat exchangers networks considering unclassified process streams at sub and above-ambient conditions

Work and heat exchanger networks have recently drawn increasing attention due to their paramount importance in achieving energy savings. In this work, we introduce a new optimization model for the cost-effective synthesis and energy integration of work and heat exchanger networks considering unclassified process streams (i.e., streams whose classification as hot or cold streams cannot be defined a priori). Our innovative modelling approach combines mathematical programming techniques and the pinch location method to obtain an optimal network design with minimal cost, while adjusting pressure and temperature levels of unclassified streams. We propose disjunctive operators for the selection of pressure manipulation equipment, and streams identity classification depending on energy requirements and process operating conditions. In addition, our approach addresses previous shortcomings by eliminating the need for: (i) assigning a specific route of pressure manipulation; and, (ii) classifying streams as low or high-pressure streams; which provides further flexibility to the system. Our methodology is also able to effectively deal with variable inlet and outlet streams temperatures to reach specific optimization goals. The model is solved to global optimality through the minimization of the process total annualized cost. Besides improved computational performance, results from energy analyses reveal that streams classification during process optimization can be greatly advantageous for both subambient and above-ambient applications. In the liquefied natural gas process, it reduces up to 89% the energy demand when compared to literature records