162 research outputs found

    MINLP model and two-stage algorithm for the simultaneous synthesis of heat exchanger networks, utility systems and heat recovery cycles

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    This work proposes a novel approach for the simultaneous synthesis of Heat Exchanger Networks (HEN) and Utility Systems of chemical processes and energy systems. Given a set of hot and cold process streams and a set of available utility systems, the method determines the optimal selection, arrangement and design of utility systems and the heat exchanger network aiming to rigorously consider the trade-off between efficiency and capital costs. The mathematical formulation uses the SYNHEAT superstructure for the HEN, and ad hoc superstructures and nonlinear models to represent the utility systems. The challenging nonconvex MINLP is solved with a two-stage algorithm. A sequential synthesis algorithm is specifically developed to generate a good starting solution. The algorithm is tested on a literature test problem and two industrial problems, the optimization of the Heat Recovery Steam Cycle of a Natural Gas Combined Cycle and the heat recovery system of an Integrated Gasification Combined Cycle. (C) 2017 Elsevier Ltd. All rights reserved

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

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    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

    Synthesis of Heat Integrated Gas Separation Systems Incorporating Absorption

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    Methodologies for simultaneous optimization of heat, mass, and power in industrial processes

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    Efficient consumption of energy and material resources, including water, is the primary focus for process industries to reduce their environmental impact. The Conference of Parties in Paris (COP21) highlighted the prominent role of industrial energy efficiency in combatting climate change by reducing greenhouse gas (GHG) emissions. Consumption of energy and material resources, especially water, are strongly interconnected; and therefore, must be treated simultaneously using a holistic approach to identify optimal solutions for efficient processing. Such approaches must consider energy and water recovery within a comprehensive process integration framework which includes options such as organic Rankine cycles for electricity generation from low to medium temperature heat. This thesis addresses the issue of how to efficiently manage energy and water in industrial processes by presenting two systematic methodologies for the simultaneous optimization of heat and mass and combined heat and power production. A novel iterative sequential solution strategy is proposed for optimizing heat-integrated water allocation networks through decomposing the overall problem into three sub-problems using mathematical programming techniques. The approach is capable of proposing a set of potential energy and water reduction opportunities that should be further evaluated for technical, economical, physical, and environmental feasibilities. A novel and comprehensive superstructure optimization methodology is proposed for organic Rankine cycle (ORC) integration in industrial processes including architectural features, such as turbine-bleeding, reheating, and transcritical cycles. Meta-heuristic optimization (via a genetic algorithm) is combined with deterministic techniques to solve the problem: by addressing fluid selection, operating condition determination, and equipment sizing. This thesis further addresses the importance of holistic approaches by applying the proposed methodologies on a kraft pulp mill. In doing so, freshwater consumption is reduced by more than 60%, while net power output is increased by a factor of six. The results exhibit that interactions among these elements are complex and therefore underline the necessity of such methods to explore their optimal integration with industrial processes. The potential implications of this work are broad, extending from total site integration to industrial symbiosis

    Heuristics with Performance Guarantees for the Minimum Number of Matches Problem in Heat Recovery Network Design

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    Heat exchanger network synthesis exploits excess heat by integrating process hot and cold streams and improves energy efficiency by reducing utility usage. Determining provably good solutions to the minimum number of matches is a bottleneck of designing a heat recovery network using the sequential method. This subproblem is an NP-hard mixed-integer linear program exhibiting combinatorial explosion in the possible hot and cold stream configurations. We explore this challenging optimization problem from a graph theoretic perspective and correlate it with other special optimization problems such as cost flow network and packing problems. In the case of a single temperature interval, we develop a new optimization formulation without problematic big-M parameters. We develop heuristic methods with performance guarantees using three approaches: (i) relaxation rounding, (ii) water filling, and (iii) greedy packing. Numerical results from a collection of 51 instances substantiate the strength of the methods

    Design of Heat Integrated Low Temperature Distillation Systems

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    Process Integration:Core processes and utility systems

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