Multi-Scale Sustainable Energy Systems Engineering

Erscheinungsjahr 2027
ISBN: 978-0-443-44934-5
Verlag: Elsevier Science

Buch, Englisch, 350 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 449 g

Multi-Scale Sustainable Energy Systems Engineering introduces a unified framework for modeling, analyzing, and optimizing complex energy systems, emphasizing interconnections across materials, processes, and sectors to accelerate future energy pathways and the energy transition. The book covers advanced mathematical algorithms, uncertainty management, machine learning, and life cycle assessment, supported by real-world case studies like renewable hydrogen production. Readers will find detailed methods for designing large-scale energy solutions such as power-chemical polygeneration, renewable integration, and supply chain planning, along with considerations for dynamic, environment-aware operations. The final sections explore the food-energy-water nexus and provide practical tutorials using the ENERGIA software platform. This self-contained resource empowers researchers, engineers, policymakers, and graduate students to develop innovative solutions for sustainable energy challenges and contribute meaningfully to the transition towards cleaner, more resilient energy systems.

Autoren/Hrsg.

Pistikopoulos, Efstratios

Tian, Yuhe

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
• Mathematik | Informatik EDV | Informatik Business Application Unternehmenssoftware
• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Verfahrenstechnik, Chemieingenieurwesen

Inhaltsverzeichnis

Part I. Energy Systems Modeling
1. Current Energy Landscape and the Energy Transition
2. Representative Energy Systems
3. Key Modeling Challenges

Part II. Energy Systems Methods and Tools
4. Mathematical Optimization
5. Optimization under Uncertainty
6. Multi-Objective Optimization
7. Machine Learning
8. Life Cycle Assessment
9. Case Study Revisit: Hydrogen Production with Renewable Energy

Part III. Energy Systems Design and Optimization
10. Power-Chemical Polygeneration Energy Systems Design under Uncertainty
11. Biomass-based Coproduction of Ammonia and Methanol
12. Optimizing Renewable Power Systems with Storage using Clustering Decomposition
13. Multi-Product Process Network Optimization with Renewable and Fossil Energy

Part IV. Sustainable Energy Transition
14. ENERGIA - An Integrated Framework for Modeling and Optimization of Energy Systems
15. Integrated Energy and Material Transition via Multi-scale Modeling and Optimization
16. Integrating Time-Varying Environmental Indicators for Enhanced Sustainability
17. Hydrogen-Based Dense Energy Carrier Supply Chain Planning

Part V. Food-Energy-Water Nexus
18. The Food-Energy-Water Nexus
19. Food: Optimal Greenhouse Farming Systems Design and Operation
20. Energy: Optimal Design of Renewable Energy Systems
21. Water: Design of Reverse Osmosis Desalination Plants
22. Revisit: The Full Integration of Food-Energy-Water Nexus

Part VI. ENERGIA Software Toolbox
23. ENERGIA Software Prototype and Hands-On Tutorials

Über Autor(innen)

Tian, Yuhe
Dr. Yuhe Tian is Assistant Professor in the Department of Chemical and Biomedical Engineering at West Virginia University. Prior to joining WVU, she received her Ph.D. degree in Chemical Engineering from Texas A&M University (2016-2021). She holds Bachelor’s degrees in Chemical Engineering and Mathematics from Tsinghua University, China (2012-2016). Her research focuses on the development and application of multi-scale systems engineering tools for modular process intensification, sustainable energy systems, advanced control and real-time decision-making.

Pistikopoulos, Efstratios
Stratos Pistikopoulos is the Director of the Texas A&M Energy Institute, and a University Distinguished Professor holding the Dow Chemical Chair in the Artie McFerrin Department of Chemical Engineering at Texas A&M University. He holds a Diploma from the Aristotle University of Thessaloniki and a Ph.D. degree from Carnegie Mellon University. His research focuses on modelling, data analysis, multiparametric control and optimization of energy, process and systems engineering & automation applications.