Advances in Digitalization and Machine Learning for Integrated Building-Transportation Energy Systems

1st Edition - November 21, 2023
Editors: Yuekuan Zhou, Jinglei Yang, Guoqiang Zhang, Peter D. Lund
Language: English
Paperback ISBN:
9 7 8 - 0 - 4 4 3 - 1 3 1 7 7 - 6
eBook ISBN:
9 7 8 - 0 - 4 4 3 - 1 3 1 7 8 - 3

Advances in Digitalization and Machine Learning for Integrated Building-Transportation Energy Systems examines the combined impact of buildings and transportation systems on energy… Read more

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Advances in Digitalization and Machine Learning for Integrated Building-Transportation Energy Systems examines the combined impact of buildings and transportation systems on energy demand and use. With a strong focus on AI and machine learning approaches, the book comprehensively discusses each part of the energy lifecycle, considering source, grid, demand, storage, and usage. Opening with an introduction to smart buildings and intelligent transportation systems, the book presents the fundamentals of AI and its application in renewable energy sources, alongside the latest technological advances.

Other topics presented include building occupants’ behavior and vehicle driving schedule with demand prediction and analysis, hybrid energy storages in buildings with AI, smart grid with energy digitalization, and prosumer-based P2P energy trading. The book concludes with discussions on blockchain technologies, IoT in smart grid operation, and the application of big data and cloud computing in integrated smart building-transportation energy systems. This title provides critical information to students, researchers, and engineers wanting to understand, design, and implement flexible energy systems to meet the rising demand in electricity.

Cover image
Title page
Table of Contents
Copyright
Dedication
List of contributors
Foreword
Preface
Acknowledgments
Chapter 1. Smart buildings and intelligent transportations with artificial intelligence and digitalization technology
Abstract
1.1 Introduction
1.2 Smart buildings
1.3 Intelligent transportations
1.4 Artificial intelligence and digitalization technology
1.5 Smart buildings and intelligent transportations with artificial intelligence and digitalization technology
1.6 Summary and future trends
References
Chapter 2. Machine learning and artificial intelligence-distributed renewable energy sources: technologies, perspectives, and challenges
Abstract
2.1 Introduction: artificial intelligence for smart energy systems
2.2 Sustainable transition with cleaner power production and machine learning
2.3 Model predictive controls with machine learning in renewable energy sources
2.4 Future prospects for machine learning in energy transition and sustainable development goals
References
Chapter 3. Building occupant behavior and vehicle driving schedules with demand prediction and analysis
Abstract
3.1 Introduction
3.2 Comprehensive literature review on occupant behavior, vehicle driving schedules, and energy analytics
3.3 Energy interaction mechanisms in integrated multienergy systems with economic feasibility
3.4 Advanced modeling techniques and guidelines for techno-economic-environmental performance improvement
References
Chapter 4. Integrated energy flexible building and e-mobility with demand-side management and model predictive control
Abstract
4.1 Introduction to integrated energy flexible building and e-mobility system
4.2 Demand-side management
4.3 Model predictive control
4.4 Challenges and future opportunities
References
Chapter 5. Electrification and hydrogenation in integrated building-transportation systems for sustainability
Abstract
5.1 Introduction
5.2 Electrification techniques
5.3 Hydrogenation techniques
5.4 Functions and mechanisms of electrification and hydrogenation in buildings
5.5 Challenges and prospects
Acknowledgment
References
Chapter 6. Hybrid energy storages in buildings with artificial intelligence
Abstract
6.1 Introduction
6.2 Commonly used energy storage systems and artificial intelligence technologies in buildings
6.3 Study cases on the application of artificial intelligence on energy storage systems in buildings
6.4 Discussion and future works
6.5 Conclusion
References
Chapter 7. Smart grid with energy digitalization
Abstract
7.1 Introduction
7.2 Smart sensor and metering technologies for energy digitalization transformation
7.3 Digital technologies for smart energy management in microgrids
7.4 Role of machine learning in energy digitalization
7.5 Future smart grid with energy digitalization and artificial intelligence
References
Chapter 8. Peer-to-peer energy trading with advanced pricing and decision-making mechanisms
Abstract
8.1 Introduction: peer-to-peer energy sharing
8.2 Peer-to-peer energy trading markets
8.3 Energy management for system participants
8.4 Advanced technologies for peer-to-peer energy trading implementation
8.5 Challenges and future works
References
Chapter 9. Blockchain technologies for automatic, secure, and tamper-proof energy trading
Abstract
Nomenclature
9.1 Introduction
9.2 Mechanisms and configurations of blockchain techniques
9.3 Data privacy and energy security in peer-to-peer energy trading
9.4 Secure and tamper-proof energy trading with blockchain and automated smart contracts
9.5 Prospects of blockchain techniques in multienergy trading platforms
Acknowledgment
References
Chapter 10. Energy economy and robustness with mobile energy storage systems
Abstract
10.1 Introduction
10.2 Model-based routing and scheduling of mobile energy storage system in coupled transportation and power distribution networks
10.3 Data-driven routing and scheduling of mobile energy storage system for electricity arbitrage
10.4 Conclusion
References
Chapter 11. Application of Internet of Energy and digitalization in smart grid and sustainability
Abstract
11.1 Introduction
11.2 Energy digitalization and Internet of Energy
11.3 Application of Internet of Energy for smart grids
11.4 Digitalized energy network for sustainability transformation
11.5 Prospects of Internet of Energy and digitalization
References
Chapter 12. Application of big data and cloud computing for the development of integrated smart building transportation energy systems
Abstract
12.1 Introduction
12.2 New energy typologies in decentralized power suppliers/consumers
12.3 Modeling development in advanced energy-information-trading networks and power-signal-cash flows
12.4 Big data, cloud computing, and digital twin in interactive multienergy networks
12.5 Challenges and future prospects of integrated smart building transportation systems
References
Chapter 13. Social and economic analysis of integrated building transportation energy system
Abstract
13.1 Introduction
13.2 Social impacts and contributions of integrated building transportation energy system
13.3 Technoeconomic analysis of integrated building transportation energy system
13.4 Implementation challenges and recommendations of integrated building transportation energy system in social and economic aspects
13.5 Conclusions and future studies
References
Index

Yuekuan Zhou

Yuekuan Zhou is an Assistant Professor of Sustainable Energy and Environment at the Hong Kong University of Science and Technology (Guangzhou), China. His research aims at achieving smart zero-energy and zero-carbon district energy systems for carbon neutrality and climate change mitigation, via cleaner power production, energy-efficient system design and operation, innovation in smart energy integration, multi-objective optimization on nonlinear dynamic behaviours with artificial intelligence. Asst. Prof. Zhou has published more than 80 papers on these topics in international, peer-reviewed journals. His current research interests include latent thermal storage, electrochemical battery, hydrogen and pumped hydro storages in zero-energy buildings, life-cycle carbon-neutral buildings, peer-to-peer energy trading and inter-city energy migration energy network with a hydrogen economy.

Affiliations and expertise

Assistant Professor, Sustainable Energy and Environment, Hong Kong University of Science and Technology (Guangzhou), China

Jinglei Yang

Prof. Jinglei Yang is an Associate Professor in the School of Mechanical and Aerospace Engineering at the Hong Kong University of Science and Technology (HKUST). For more than 20 years, he has conducted research in the fields of materials science and mechanics of materials. He has also worked on nano- and micro-encapsulation for a variety of applications, including self-healing materials, thermal regulating materials, and antibacterial and wear-resistant/self-lubricating polymers, FRP composites, fiber-metal laminates, nanocomposites, stimuli-responsive polymers, and mechanics. He has multidisciplinary expertise in a variety of fields, including chemical synthesis, production, thermal analysis, and mechanical characterization. He has developed a novel technique to microencapsulate different chemicals and reagents for multipurpose applications. His most recent accomplishments include being named to the Top 1 percent of international materials scientists from the Stanford-Ranking List for the year 2020 and being elected as a Fellow of the Royal Society of Chemistry and Royal Aeronautical Society in 2021. He is currently in charge of more than 30 team members and has completed or is managing more than 30 projects.

Affiliations and expertise

Associate Professor, School of Mechanical and Aerospace Engineering, Hong Kong University of Science and Technology (HKUST), Hong Kong, China

Guoqiang Zhang

Prof. Zhang was the national candidate of the New Century Talents project, an innovative promotion plan of the Ministry of Science and Technology of China. His areas of expertise include indoor air quality, district energy systems, and high-quality, sustainable construction, and his work has received recognition at a national and international level. Prof. Zhang is the founding scientist of the China Construction 4.0 – Sustainable Urbanization and Construction Innovation Platform, but also serves as Dean of the Institute of Sustainable Urbanization and Construction Innovation at Hunan University and as Director of the National Center for International Research Collaboration in Building Safety and Environment of the People’s Republic of China.

Affiliations and expertise

Professor, College of Civil Engineering; Dean, Institute of Sustainable Urbanization and Construction Innovation, Hunan University, Changsha, Hunan Province, China

Peter D. Lund

Peter Lund is Professor in Advanced Energy Systems at Aalto University, Finland. He has about 40 years of experience in energy technology, innovations, systems, and policy. Dr. Lund has worked as a visiting professor at Southeast University, Technical University of Dresden (Germany), and Hubei University (Wuhan) (Nanjing). He served as the chair of the European Commission's Energy Advisory Group from 2002 to 2006. He also serves as the chair of the Energy Steering Panel of the European Academies Science Advisory Council (EASAC) and is a participant in the Euro-CASE and European University Association energy platforms (European Council of Applied Sciences Technologies and Engineering). Prof. Lund has provided advice to numerous companies and international energy programs, including the International Energy Agency. He is a member of the Swedish Engineering Academy in Finland and the Editor-Europe of the journal Energy Research and Interdisciplinary Reviews: Energy and Environment. He regularly gives lectures on energy all over the world and has published more than 500 research publications. He has received several awards from around the world, most recently the Jinling Award in 2016.

Affiliations and expertise

Professor in Advanced Energy Systems, Aalto University, Finland