Optimization of Sustainable Process Systems

Nyhet

Multiscale Models and Uncertainties

Inbunden, Engelska, 2026

2 349 kr

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Presents a systematic review of optimizing sustainable process systems through multiscale modeling and uncertainty analysis The global pursuit of net-zero carbon emissions has created an urgent need for chemical engineers and energy researchers to design systems that are both sustainable and resilient. While renewable energy sources such as solar and wind offer great potential, their variability introduces significant challenges that must be addressed through advanced optimization techniques. Optimization of Sustainable Process Systems: Multiscale Models and Uncertainties connects optimization fundamentals with their applications in sustainable energy systems with a particular emphasis on the challenges posed by uncertainty. Divided into two parts, the book first introduces the core mathematical frameworks and methods needed to model and optimize uncertain systems, including stochastic programming, robust optimization, reinforcement learning, and multiscale algorithms. The authors clearly explain these state-of-the-art tools with attention to both theory and computational practice. The second part shifts to applications, demonstrating how these techniques are applied in real-world contexts such as renewable-based hydrogen, methanol, and ammonia production; carbon capture; shale gas systems; biomass integration; and power system optimization. Throughout the text, the authors emphasize the integration of renewables with chemical industries while highlighting strategies to manage variability, strengthen supply chains, and improve system-wide efficiency. Combining rigorous fundamentals with cutting-edge applications through a tutorial-style approach, Optimization of Sustainable Process Systems: Multiscale Models and Uncertainties: Provides the foundation and tools needed to design resilient, optimized, and sustainable energy systemsAddresses optimization methods under uncertainty tailored to energy and process systemsPresents a unified treatment of stochastic programming, robust optimization, and reinforcement learning techniquesIntegrates renewable-based systems with chemical industry supply chain design and operationAddresses computational challenges in large-scale optimization of energy systemsBoth a theoretical resource and a practical guide for applied problem-solving, Optimization of Sustainable Process Systems: Multiscale Models and Uncertainties is ideal for graduate-level courses in chemical engineering, process systems engineering, energy systems optimization, and operations research. It is also a valuable reference for industrial researchers, system modelers, and developers working on sustainable process design and energy transition strategies.

Produktinformation

Utgivningsdatum2026-05-21
FormatInbunden
SpråkEngelska
Antal sidor400
Upplaga26001
FörlagJohn Wiley & Sons Inc
ISBN9781394205578

Tillhör följande kategorier

Energiindustri inom Ekonomi och Ledarskap
Energiteknik inom Naturvetenskap och teknik

List of Contributors xiiiPreface xvii1 An Introduction to Bilevel Optimization and Its Application to Sustainable Systems Engineering 1Rishabh Gupta, Jnana S. Jagana, Tushar Rathi, and Qi Zhang1.1 Introduction 11.2 Fundamentals of Bilevel Optimization 21.3 Some Applications in Sustainable Systems Engineering 121.4 Bilevel Optimization for Machine Learning 141.5 Robust Optimization 251.6 Conclusions 332 Exploiting the Multiscale Structure of Sustainable Engineering Problems via Network-Based Decomposition 43Ilias Mitrai and Prodromos Daoutidis2.1 Introduction 432.2 Learning the Structure of Optimization Problems 452.3 Network-Based Decomposition of Optimization Problems 482.4 Case Study: Transition to Green Ammonia Supply Chain Networks 522.5 Conclusions 573 Multi-Objective Bayesian Optimization for Networked Black-Box Systems: A Path to Greener Profits and Smarter Designs 63Akshay Kudva, Wei-Ting Tang, and Joel A. Paulson3.1 Introduction 633.2 Problem Formulation 663.3 Multi-Objective Bayesian Optimization Over Network Systems 683.4 Case Studies 753.5 Conclusion 844 A Tutorial on Multi-time Scale Optimization Models and Algorithms 91Asha Ramanujam and Can Li4.1 Introduction 914.2 Multi-time Scale Optimization Models 924.3 Value of the Multi-scale Model (VMM) 944.4 Algorithms to Solve Multi-time Scale Optimization Models 964.5 Illustrative Example 1194.6 Conclusion 1295 Many Objective Optimization Tools for Sustainable Decision-Making 135Andrew Allman and Hongxuan Wang5.1 Introduction 1355.2 Sustainability Objectives 1365.3 MOP Solution Methods 1385.4 Objective Dimensionality Reduction for MaOPs 1415.5 Case Study: Cost Versus Emissions-Driven Demand Response 1445.6 Case Study: Analysis of Planetary Boundary Objectives 1475.7 Conclusion and Future Perspectives 1506 Optimization Models and Algorithms for Design and Planning of Sustainable Processes and Energy Systems 155Seolhee Cho and Ignacio E. Grossmann6.1 Introduction 1556.2 Optimization Models 1566.3 Solution Strategies 1606.4 Algebraic Modeling Languages 1626.5 Applications in Sustainable Process and Energy Systems 1646.6 Conclusions 1697 Multiscale Modeling and Optimization of Carbon Capture Processes 179Kyeongjun Seo, Mark A. Stadtherr, and Michael Baldea7.1 Introduction 1797.2 Modeling of Carbon Capture Processes 1807.3 Multiscale Modeling and Optimization Results 1877.4 Conclusions 1938 Integrated Design and Operability Optimization of Sustainable Process Intensification Systems 199Yuhe Tian, Rahul Bindlish, and Efstratios N. Pistikopoulos8.1 Introduction 1998.2 Methodology Framework 2028.3 Case Studies 2108.4 Concluding Remarks 2189 Circular Economy Assessment Tools for Process Systems 223Paola Munoz-Briones, Kenneth Martinez, Javiera Vergara-Zambrano, and Styliani Avraamidou9.1 Introduction 2239.2 Circular Economy Assessment in the Food Sector 2269.3 Circular Economy Assessment in the Chemical Industry 2329.4 Circular Economy Metrics for Energy Systems 23710 Decarbonization of Steam Cracking for Clean Olefins Production: Optimal Microgrid Scheduling 251Saba Ghasemi Naraghi, Tylee Kareck, Lingyun Xiao, Richard Reed, Paritosh Ramanan, and Zheyu Jiang10.1 Introduction 25110.2 Dynamic Optimization of Steam Cracking Process 25410.3 Scenario-Based Optimal Microgrid Scheduling Problem 25810.4 Illustrative Case Studies 26510.5 Conclusion 27511 Multiscale Strategies for the Use of Chemicals as Energy Storage Systems 279Diego Santamaría, Antonio Sánchez, and Mariano Martín11.1 Introduction 27911.2 Methodology 27911.3 Cases of Study 28511.4 Conclusions 30412 Repurposing a Conventional Oil Refinery for Biomass Processing to Aviation Fuel: Process Design and Techno-Environmental Evaluation for a Real Operating Plant 317Valeria González, Alejandro Pedezert, Soledad Gutiérrez, Roberto Kreimerman, Lucia Pittaluga, and Ana I. Torres12.1 Introduction 31712.2 Overview of Feed Options, Processing Pathways and Current Infrastructure 31912.3 Sustainable Aviation Fuel Process Design 32112.4 Sustainable Aviation Fuel Process Design: Adjustments in Design to Match Current Operations in the Refinery 33312.5 Environmental Assessment Using GREENSCOPE 33712.6 Summary and Final Remarks 34313 Uncertainty Quantification of Solid Sorbent-Based CO2 Capture Processes 349Ana Flávia Monteiro and Debangsu Bhattacharyya13.1 Introduction 34913.2 Methodology 35213.3 Example-UQ of a Solid-Based CO2 Capture System in a Fixed Bed 35613.4 Concluding Remarks 363References 366Index 371