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)

Integration of different models in the design of chemical processes: Application to the design of a power plant

With advances in the synthesis and design of chemical processes there is an increasing need for more complex mathematical models with which to screen the alternatives that constitute accurate and reliable process models. Despite the wide availability of sophisticated tools for simulation, optimization and synthesis of chemical processes, the user is frequently interested in using the ‘best available model’. However, in practice, these models are usually little more than a black box with a rigid input–output structure. In this paper we propose to tackle all these models using generalized disjunctive programming to capture the numerical characteristics of each model (in equation form, modular, noisy, etc.) and to deal with each of them according to their individual characteristics. The result is a hybrid modular–equation based approach that allows synthesizing complex processes using different models in a robust and reliable way. The capabilities of the proposed approach are discussed with a case study: the design of a utility system power plant that has been decomposed into its constitutive elements, each treated differently numerically. And finally, numerical results and conclusions are presented.Spanish Ministry of Science and Innovation (CTQ2012-37039-C02-02)

Large scale optimization of a sour water stripping plant using surrogate models

In this work, we propose a new methodology for the large scale optimization and process integration of complex chemical processes that have been simulated using modular chemical process simulators. Units with significant numerical noise or large CPU times are substituted by surrogate models based on Kriging interpolation. Using a degree of freedom analysis, some of those units can be aggregated into a single unit to reduce the complexity of the resulting model. As a result, we solve a hybrid simulation-optimization model formed by units in the original flowsheet, Kriging models, and explicit equations. We present a case study of the optimization of a sour water stripping plant in which we simultaneously consider economics, heat integration and environmental impact using the ReCiPe indicator, which incorporates the recent advances made in Life Cycle Assessment (LCA). The optimization strategy guarantees the convergence to a local optimum inside the tolerance of the numerical noise.The authors wish to acknowledge the financial support by the Ministry of Economy and Competitiveness of Spain, under the project CTQ2012-37039-C02-02

Optimization of the design, operating conditions, and coupling configuration of combined cycle power plants and CO2 capture processes by minimizing the mitigation cost

This paper deals with the optimization of the coupling between a natural gas combined cycle (NGCC) plant and a post-combustion CO2 capture process by minimizing the mitigation cost – defined as the ratio between the cost of electric power generation and the amount of CO2 emitted per unit of total net electric power generated – while satisfying the design specifications: electric power generation capacity and CO2 capture level. Three candidate coupling configurations, which differ in the place where the steam is extracted from, are optimized using detailed and rigorous models for both the NGCC and the CO2 capture plants. By comparing the mitigation cost of each configuration, the optimal integration configuration and the corresponding optimal sizes and operating conditions of all process units (steam turbines, gas turbines, heat recovery steam generators HRSGs, absorption and regeneration columns, reboilers and condensers, and pumps) are provided. In the computed optimal solution, the steam required by the CO2 capture plant is extracted from both the steam turbine and the HRSG (evaporator operating at low pressure), and the mitigation cost is 90.88 $/t CO2. The optimal solution is compared with suboptimal solutions corresponding to the other two candidate coupling schemes. These solutions are compared in detail regarding capital investment and operating costs, HRSG configuration, process unit sizes, and operating conditions.The financial support from the Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) and the Facultad Regional Rosario of the Universidad Tecnológica Nacional from Argentina are gratefully acknowledged

Design and Optimization of Carbon Dioxide Capture and Storage Process for Low-carbon Power Generation

학위논문 (박사)-- 서울대학교 대학원 공과대학 화학생물공학부, 2017. 8. 한종훈.Carbon capture and storage (CCS) technologies have been considered a realistic option for mitigating the climate change. Post-combustion CO2 capture utilizes existing coal-fired power plants, and aqueous monoethanolamine (MEA) scrubbing is the most well proven capture technology. However, the heat and energy requirements of solvent regeneration and CO2 liquefaction cause a 30% decrease in net power output. This power de-rate is a major obstacle for implementing CCS. Herein, the energy efficient and economical carbon capture, compression, dehydration, liquefaction and injection process is proposed. Firstly, simulation-based parametric optimization is performed to minimize the power de-rate. Post-combustion CO2 capture with aqueous MEA scrubbing (85 %, 90 %, and 95 % removals) and CO2 liquefaction integrated with a 550 MWe supercritical coal-fired power plant is simulated. The liquid to gas ratio and stripper operating pressure of the CO2 capture process are the selected manipulated variables with steam extracted from the IP-LP crossover pipe and the first LP turbine as possible heat sources. The power de-rate was reduced to 17.7 % when operating at optimum conditions. In addition, the author propose a comprehensive optimal design of CO2 dehydration process using a superstructure-based optimization. The superstructure model development includes binary interaction parameter regression for NRTL-RK thermodynamic model, unit operation modeling, and identification of all connectivity of the unit operations in the superstructure. The superstructure imbeds 30,720 possible process alternatives, and the optimum process configuration with the least cost and its operating condition are simultaneously identified using Aspen Plus-MATLAB interface. The optimum process includes three-stage contactor, ten-stage still column, lean/rich solvent heat exchanger, and cold rich solvent split flow fed to the sixth-stage of still column. The total annualized cost of the optimum process is 5.67 M$/yr, and it corresponds to the specific annualized cost of 1.80$/tonCO2. Sensitivity analysis using Monte Carlo simulation is also presented for the optimum process, and the refrigerant and steam are the most influential utility costs. Lastly, the small-scale topside CO2 injection process for offshore platform is designed from conceptual design to piping & instrument diagram level with the hazard and operability study is presented.CHAPTER 1. Introduction 1 1.1. Research motivation 1 1.2. Research objectives 3 1.3. Outline of the thesis 4 CHAPTER 2. Energy Penalty Reduction in Coal-fired Power Plant with Post-combustion CO2 Capture and Liquefaction Process 6 2.1. Overview 6 2.1.1. Methodology 11 2.2. Process Description 13 2.2.1. Steam Cycle 13 2.2.2. CO2 Capture Process 17 2.2.3. Self-refrigerant CO2 Liquefaction 26 2.3. Integration of Steam Cycle with CO2 Capture and Liquefaction Process 30 2.3.1. Definition of Power De-rate 30 2.3.2. Steam Extraction from an Existing Power Plant 31 2.3.3. Variable Selection 36 2.4. Results and Discussion 38 2.4.1. CO2 Capture Process 38 2.4.2. Liquefaction Process for Shipping 49 2.4.3. Power De-rate Reduction 51 CHAPTER 3. Design of Carbon Dioxide Dehydration Process using Derivative-free Superstructure Optimization 60 3.1. Overview 60 3.2. Modeling Basis 65 3.2.1. Design Specification 65 3.2.2. Thermodynamic Model 66 3.2.3. Data Regression and Validation 67 3.3. Design of Superstructure 71 3.3.1. Compression Process 72 3.3.2. Dehydration Process 73 3.4. Process Optimization 79 3.4.1. Preprocessing & Screening 79 3.4.2. Optimization Problem Formulation 80 3.4.3. Genetic Algorithm Interface Setting and Execution 83 3.5. Results and Discussion 84 3.5.1. Optimization Results 84 3.5.2. Thermodynamic Evaluation 89 3.5.3. Economic Evaluation 90 3.5.4. Sensitivity Analysis 91 CHAPTER 4. Design of CO2 Injection Topside Process for Offshore Platform in Pohang, South Korea 101 4.1. Overview 101 4.2. Process Description 106 4.3. Hazard and Operability (HAZOP) Analysis 110 4.3.1. Node Selection 116 4.3.1. Result and Discussion 120 CHAPTER 5. Concluding Remarks 126 5.1. Conclusions 126 Reference 130 Appendix 142 A. HAZOP Worksheet 142 Nomenclature 163 Abstract in Korean (국문초록) 167Docto

An investigation into the feasibility of integrating intermediate-temperature solid oxide electrolysers with power plants

The detrimental effect of increasing global emissions of CO2 on the environment has prompted action to be taken to improve the environmental impact of hydrocarbon-based processes and fuel use. Therefore, producing hydrogen as an alternative fuel for vehicles fitted with fuel cells through solid oxide electrolyser cells (SOECs) has been considered. Coal fired power plants are major energy providers and are operational all day. Introducing SOECs into the plant to utilise hot steam and electricity during times of low energy demand may provide a step to large scale hydrogen production. Through modelling and experimentation of power plants and SOECs, this project aims to evaluate the feasibility of an integrated system based on the thermodynamic, techno-economic and SOEC performance analyses. Results show that SOECs, which operate between 600 and 1000 °C, take advantage of the heat of the steam, which increases electrolyser efficiency. Steam from before the intermediate pressure turbine at 560 °C and 46 atm was located from a simulation of a coal fired power plant. The intermediate-temperature steam of the plant was applicable to less used Gd-doped CeO2 (CGO) than yttria stabilised zirconia (YSZ) electrolyte that performs best at 900 °C, as shown experimentally. Modelling showed SOEC efficiency was improved by 25.2 % through an integrated system rather than traditional methods of heating water to steam, due to reduced energy requirements. Furthermore, the thermoneutral point of 4,644 A m -2 (1.31 V) formed a guide for the design and operation of SOECs. Analysis on the integrated system showed that 250 MW (7500 kg hr-1) and 290 MW (8700 kg hr-1) H2 can be produced with SOECs sized at 43,300 and 50,100 m -2, respectively, for scenarios of 7% steam extraction and a purely H2 production plant, at a cost of 3.76 $ kg H2-1. Although an integrated system shows promise for large scale hydrogen production, further development for suitable electrolytes and hydrogen storage and infrastructure is required

Reducción de las emisiones de gases con efecto invernadero (GEIs) en el sector energético mediante tecnologías no convencionales

Históricamente, en la provincia de Santa Fe las demandas de electricidad se satisfacen importando energía generada en otras provincias ya que carece de una matriz energética propia. Se conoce que en Argentina el 52 % de la electricidad se produce en centrales térmicas, que funcionan a gas o diesel; el 43 % en usinas hidroeléctricas, y apenas el 4 % es energía nuclear. A partir del año 2003 las demandas eléctricas en la mayoría de las provincias, incluyendo Santa Fe, se incrementaron fuertemente como consecuencia del crecimiento económico experimentado en diferentes sectores productivos tales como el agro, la construcción y la industria. Esto obligó tanto al gobierno nacional como provincial a impulsar un nuevo plan estratégico con el principal objetivo de aumentar la producción de electricidad y así poder reducir los efectos negativos de la crisis energética que afecta a todo el territorio nacional. A pesar de que las centrales de ciclo combinado operan con gas natural y en consecuencia son las que menos contaminan respecto a plantas que operan con carbón, requieren que los gases de combustión generados deban ser tratados necesariamente antes de ser emitidos al ambiente. La corriente de gases exhaustos contiene uno de los principales responsables del calentamiento global, el CO2. Diferentes estudios revelan que para las próximas décadas la concentración de CO2 en el ambiente aumentaría a ritmos más acelerados en caso que no se adopten las medidas y acciones necesarias tendientes a disminuir dichas emisiones. De este modo resulta evidente la imperiosa necesidad de investigar y proponer soluciones efectivas para reducir las emisiones de gases con efecto invernadero. Algunas de las acciones tendientes a reducir las emisiones de CO2 procedentes de la combustión de combustibles fósiles para la producción de energía, debieran apuntar a: 1) uso racional de la energía generada (aumento de la eficiencia en los procesos de conversión), 2) utilizar combustibles que tengan menores emisiones (energías renovables, gas natural), 3) captura y almacenamiento del CO2 procedente de la combustión. En este sentido, esta tesis se enmarca en el punto 3) ya que se propone investigar y desarrollar procesos eficientes para tratar las emisiones generadas en las plantas de producción de energía eléctrica que contribuyen al efecto invernadero, en especial el CO2.Fil: Arias, Ana Marisa. UTN. FRRo. CAIMI; ArgentinaPeer Reviewe