Description
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 systems
- Addresses optimization methods under uncertainty tailored to energy and process systems
- Presents a unified treatment of stochastic programming, robust optimization, and reinforcement learning techniques
- Integrates renewable-based systems with chemical industry supply chain design and operation
- Addresses computational challenges in large-scale optimization of energy systems
Both 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.
Table of Contents
List of Contributors xiii
Preface xvii
1 An Introduction to Bilevel Optimization and Its Application to Sustainable Systems Engineering 1
Rishabh Gupta, Jnana S. Jagana, Tushar Rathi, and Qi Zhang
1.1 Introduction 1
1.2 Fundamentals of Bilevel Optimization 2
1.3 Some Applications in Sustainable Systems Engineering 12
1.4 Bilevel Optimization for Machine Learning 14
1.5 Robust Optimization 25
1.6 Conclusions 33
2 Exploiting the Multiscale Structure of Sustainable Engineering Problems via Network-Based Decomposition 43
Ilias Mitrai and Prodromos Daoutidis
2.1 Introduction 43
2.2 Learning the Structure of Optimization Problems 45
2.3 Network-Based Decomposition of Optimization Problems 48
2.4 Case Study: Transition to Green Ammonia Supply Chain Networks 52
2.5 Conclusions 57
3 Multi-Objective Bayesian Optimization for Networked Black-Box Systems: A Path to Greener Profits and Smarter Designs 63
Akshay Kudva, Wei-Ting Tang, and Joel A. Paulson
3.1 Introduction 63
3.2 Problem Formulation 66
3.3 Multi-Objective Bayesian Optimization Over Network Systems 68
3.4 Case Studies 75
3.5 Conclusion 84
4 A Tutorial on Multi-time Scale Optimization Models and Algorithms 91
Asha Ramanujam and Can Li
4.1 Introduction 91
4.2 Multi-time Scale Optimization Models 92
4.3 Value of the Multi-scale Model (VMM) 94
4.4 Algorithms to Solve Multi-time Scale Optimization Models 96
4.5 Illustrative Example 119
4.6 Conclusion 129
5 Many Objective Optimization Tools for Sustainable Decision-Making 135
Andrew Allman and Hongxuan Wang
5.1 Introduction 135
5.2 Sustainability Objectives 136
5.3 MOP Solution Methods 138
5.4 Objective Dimensionality Reduction for MaOPs 141
5.5 Case Study: Cost Versus Emissions-Driven Demand Response 144
5.6 Case Study: Analysis of Planetary Boundary Objectives 147
5.7 Conclusion and Future Perspectives 150
6 Optimization Models and Algorithms for Design and Planning of Sustainable Processes and Energy Systems 155
Seolhee Cho and Ignacio E. Grossmann
6.1 Introduction 155
6.2 Optimization Models 156
6.3 Solution Strategies 160
6.4 Algebraic Modeling Languages 162
6.5 Applications in Sustainable Process and Energy Systems 164
6.6 Conclusions 169
7 Multiscale Modeling and Optimization of Carbon Capture Processes 179
Kyeongjun Seo, Mark A. Stadtherr, and Michael Baldea
7.1 Introduction 179
7.2 Modeling of Carbon Capture Processes 180
7.3 Multiscale Modeling and Optimization Results 187
7.4 Conclusions 193
8 Integrated Design and Operability Optimization of Sustainable Process Intensification Systems 199
Yuhe Tian, Rahul Bindlish, and Efstratios N. Pistikopoulos
8.1 Introduction 199
8.2 Methodology Framework 202
8.3 Case Studies 210
8.4 Concluding Remarks 218
9 Circular Economy Assessment Tools for Process Systems 223
Paola Munoz-Briones, Kenneth Martinez, Javiera Vergara-Zambrano, and Styliani Avraamidou
9.1 Introduction 223
9.2 Circular Economy Assessment in the Food Sector 226
9.3 Circular Economy Assessment in the Chemical Industry 232
9.4 Circular Economy Metrics for Energy Systems 237
10 Decarbonization of Steam Cracking for Clean Olefins Production: Optimal Microgrid Scheduling 251
Saba Ghasemi Naraghi, Tylee Kareck, Lingyun Xiao, Richard Reed, Paritosh Ramanan, and Zheyu Jiang
10.1 Introduction 251
10.2 Dynamic Optimization of Steam Cracking Process 254
10.3 Scenario-Based Optimal Microgrid Scheduling Problem 258
10.4 Illustrative Case Studies 265
10.5 Conclusion 275
11 Multiscale Strategies for the Use of Chemicals as Energy Storage Systems 279
Diego Santamaría, Antonio Sánchez, and Mariano Martín
11.1 Introduction 279
11.2 Methodology 279
11.3 Cases of Study 285
11.4 Conclusions 304
12 Repurposing a Conventional Oil Refinery for Biomass Processing to Aviation Fuel: Process Design and Techno-Environmental Evaluation for a Real Operating Plant 317
Valeria González, Alejandro Pedezert, Soledad Gutiérrez, Roberto Kreimerman, Lucia Pittaluga, and Ana I. Torres
12.1 Introduction 317
12.2 Overview of Feed Options, Processing Pathways and Current Infrastructure 319
12.3 Sustainable Aviation Fuel Process Design 321
12.4 Sustainable Aviation Fuel Process Design: Adjustments in Design to Match Current Operations in the Refinery 333
12.5 Environmental Assessment Using GREENSCOPE 337
12.6 Summary and Final Remarks 343
13 Uncertainty Quantification of Solid Sorbent-Based CO2 Capture Processes 349
Ana Flávia Monteiro and Debangsu Bhattacharyya
13.1 Introduction 349
13.2 Methodology 352
13.3 Example-UQ of a Solid-Based CO2 Capture System in a Fixed Bed 356
13.4 Concluding Remarks 363
References 366
Index 371
