Facultad Regional Rosario

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Author: search.filters.author.Manassaldi, Juan Ignacio

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    Renewable energy-water nexus: optimal design of an integrated system including a single flash geothermal plant, kalina cycle and reverse Osmosis desalination unit
    (2023-12) Manassaldi, Juan Ignacio; Mussati, Miguel Ceferino; Incer-Valverde, Jimena; Morosuk, Tatiana; Mussati, Sergio Fabián
    Resumen de artículo presentado en la Conferencia. This paper addresses the optimization of a dual-purpose desalination system based on a geothermal flash cycle, Kalina cycle, and a reverse osmosis seawater desalination plant. A nonlinear mathematical programming (NLP) optimization is developed and implemented in GAMS – general algebraic modeling system – which is a high-level modeling environment widely used in Process System Engineering PSE. CONOPT, which is a derivate-based optimization algorithm, is used as an NLP solver. Also, dynamic-link libraries (DLLs) are developed and implemented in the programming code C with the aim of rigorously calculating the thermodynamic properties of all process streams. The DLLs are systematically called from the GAMS environment. In addition, a solution strategy has been developed to facilitate model convergence. In this approach, several models are sequentially solved, starting with the simplest model progressing to solving a more complex model. As a result, the optimal sizing and operating conditions of all process units are simultaneously obtained. Finally, a sensitivity analysis of the key model parameters, electrical power, and freshwater demands on the optimization criterion is discussed. The proposed mathematical model is a powerful decision-making tool for the design and synthesis of integrated geothermal power and desalination processes, which can be used as either a simulator or an optimizer, depending on the number of freedom degrees specified by the user.
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    Optimization of the design, operating conditions, and coupling configuration of combined cycle power plants and CO2 capture processes by minimizing the mitigation cost.
    (2017-10-04) Mores, Patricia Liliana; Manassaldi, Juan Ignacio; Scenna, Nicolás José; Caballero, José Antonio; Mussati, Miguel Ceferino; Mussati, Sergio Fabián
    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.
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    Development of extrinsic functions for optimal synthesis and design : application to distillation-based separation processes.
    (2019-04-09) Manassaldi, Juan Ignacio; Mussati, Miguel Ceferino; Scenna, Nicolás José; Mussati, Sergio Fabián
    This work deals with the development and implementation of mathematical models in the General Algebraic Modeling System (GAMS) environment for optimization purposes, involving extrinsic functions that are executed outside GAMS from dynamic-link libraries (DLL) implemented in the programming language C. Three DLL libraries are developed to calculate thermodynamic properties: the Raoult's law for vapor-liquid equilibrium, the Non-Random Two-Liquid (NRTL) model, and the Peng–Robinson equation of state. A detailed description on how GAMS and DLL libraries interact is presented. Case studies dealing with the optimal design of multi-component distillation columns with increasing complexity levels are discussed. For the proposed case studies, the obtained results show that the usage of the proposed extrinsic functions allows to significantly enhance the model implementation compared to the traditional model implementation approach, and to considerably reduce the model size as well as the computational time required by the optimization algorithms.
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    Optimization of triple-pressure combined-cycle power plants by generalized disjunctive programming and extrinsic functions.
    (2021-02-01) Manassaldi, Juan Ignacio; Mussati, Miguel Ceferino; Scenna, Nicolás José; Mussati, Sergio Fabián
    A new mathematical framework for optimal synthesis, design, and operation of triple-pressure steamreheat 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.
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    Process optimization and revamping of combined-cycle heat and power plants integrated with thermal desalination processes.
    (2021-06-06) Manassaldi, Juan Ignacio; Mussati, Miguel Ceferino; Scenna, Nicolás José; Morosuk, Tatiana; Mussati, Sergio Fabián
    Optimal revamping, sizing, and operation of an existing gas-turbine combined-cycle dual-purpose power/desalination plant – simultaneous electricity and freshwater generation – which operates with a heat recovery steam generation with one-pressure level (1P-HRSG) and a multi-stage flash desalination process, is addressed. The sizes and configurations of the gas turbine and desalination unit are kept the same as in the existing plant through the study. However, the 1P-HRSG is conveniently extended to twoor three-pressure levels with different exchanger arrangements, including steam reheating. To this end, a superstructure-based representation of the HRSG simultaneously embedding several candidate structures was proposed and a mixed-integer nonlinear programming model was derived from it. One revamping case consisted in maximizing the ratio between the freshwater production rate and the heat transfer area of HRSG, keeping unchanged the electricity generation rate (around 73 MW). It was found that the inclusion of a 3P-HRSG resulted in an increase of 13.782 kg⋅s−1 in the freshwater production, requiring 22753 m2 of heat transfer area less in the HRSG. Another revamping case consisted in maximizing the profit, contemplating the possibility to sell extra amounts of electricity and freshwater. Sale prices, for which producing extra electricity and freshwater is beneficial, were determined.
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    Aplicación de técnicas de programación matemática y métodos de integración de procesos para determinar la síntesis y el diseño óptimo de una planta de cogeneración de ciclo combinado
    (2017-03-29) Manassaldi, Juan Ignacio; Mussati, Sergio Fabián; Scenna, Nicolás José
    La presente tesis trata sobre el modelado matemático, simulación y optimización de ciclos combinados operando en forma desacoplada y acoplada a otros procesos, como por ejemplo, sistemas de utility y planta de captura de CO2. Precisamente, la tesis presenta modelos matemáticos utilizando programación matemática y metodologías “alternativas” para optimizar la configuración y el diseño de sistemas de cogeneración de vapor y electricidad. El planteamiento del problema de optimización se resolverá postulando una superestructura de configuraciones alternativas considerando la posibilidad de intercambios de calor en paralelo, serie y serie-paralelo entre la corriente de gas que abandona la turbina de gas y el fluido circulante del ciclo de vapor. De esta manera, la superestructura embebe numerosas alternativas para la configuración de los equipos las cuales son tenidas en cuenta simultáneamente por el algoritmo de optimización. La ventaja principal de este tipo de planteo es que al modificar las especificaciones de diseño permite determinar en forma automática la configuración óptima correspondiente. Durante el desarrollo de la tesis, se proponen y resuelven diferentes problemas de optimización considerando diferentes funciones objetivos y considerando fija la demanda de electricidad, según se detalla a continuación: 1) minimización del área total de transferencia de calor, 2) minimización del consumo de combustible, 3) minimización del costo total (inversión y costo de operación). Los modelos y metodologías de solución se aplican a la optimización de la configuración, diseño y operación de un sistema de cogeneración acoplado a distintos procesos, por ejemplo a un proceso de captura de CO2 utilizando aminas. Finalmente, la metodología es aplicada también para optimizar la síntesis y diseño de plantas de “utility” (configuración del ciclo combinado y configuración del sistema de turbinas y válvulas) considerando diferentes niveles de demandas de potencia y vapor. Las metodologías de solución se componen de procedimientos sistemáticos basados en el empleo de técnicas de Programación Mixta Entera No Lineal (MINLP), utilizando variables binarias para imponer restricciones de diseño de tipo estructural (configuración de los equipos) y variables continúas relacionadas con las condiciones de operación. Los resultados encontrados son comparados con los obtenidos por otros resolvedores tradicionales para modelos MINLP.