Integration of Energy, Information, Transportation and Humanity: Renaissance from Digitization

By C.C. Chan, George You Zhou and Wei Han

Focusing on energy, transportation, information, and economic networks and flows, Integration of Energy, Information,Transportation and Humanity uniquely examines the interconnection, interaction, and integration across these multiple sectors. It helps readers understand the correlation of energy, transportation, and information via the integration of humanity world, cyber world and physical world. It clearly explains the objectives of the integration of energy network, transportation network, information network, humanity network, as well as the integration of energy flow, information flow, material flow and value flow (4N4F); the philosophy, science, and engineering of the integration of 4N4F; the mechanism, keys and benefits of the integration of 4N4F; the carriers of the integration of 4N4F; and the framework of the integration of 4N4F.

• Synthesizes the newest developments in digital technologies and digital economy
• Includes case studies and examples that illustrate the application of methodologies and technologies employed
• Useful for both theoretically and technically oriented researchers

• Language: English
• Publisher: Elsevier Science
• Release date: Oct 11, 2023
• ISBN: 9780323955225

C.C. Chan

Prof. C. C. Chan holds BSc, MSc, PhD, HonDSc, HonDTech degrees. He is an authority on the integration of humanity world, cyber world, and physical world, and an honorary professor at the University of Hong Kong. He is the founder of International Academicians Science and Technology Innovation Centre; Visiting Professor of MIT, UC Berkeley, University of Cambridge, and others; founding and Rotating President of the World Electric Vehicle Association; Senior Consultant to governments, academia and industries; Academician of Chinese Academy of Engineering, Fellow of Royal Academy of Engineering, U.K., Fellow of Ukraine Academy of Engineering Sciences, Honorary Fellow of Hungarian Academy of Engineering, Life Fellow of IEEE, Fellow of IET, and Honorary Fellow of HKIE; Recipient of the Royal Academy of Engineering Prince Philip Medal, Chinese Academy of Engineering Guang-Hua Prize; World Federation of Engineering (WFEO) Medal of Engineering Excellence; Silver Bauhinia Star Medal of the Hong Kong Special Administrative Region Government; Gold Medal of Hong Kong Institution of Engineers; IEEE Transportation Technologies Award; and “Father of Asian Electric Vehicles” by Magazine Global View. His major research field includes the philosophy and key technologies of electric vehicles and intelligent energy systems. He has published 17 books, over 450 technical papers and holds 10 patents.

Book preview

Introduction

Focusing on energy, transportation, information, and economic networks and flows, Integration of Energy, Information, Transportation and Humanity uniquely examines the interconnection, interaction, and integration across these multiple sectors. It helps readers understand the correlation of energy, transportation, and information via the integration of humanistic, cyber, and physical worlds. It clearly explains the objectives of the integration of energy, transportation, information, and humanity networks, as well as the integration of energy, information, material, and value flows (4N4F); the philosophy, science, and engineering of the integration of 4N4F; the mechanism, keys, and benefits of the integration of 4N4F; the carriers of the integration of 4N4F; and the framework of the integration of 4N4F.

The key features of the book include (1) the syntheses of the newest developments in digital technologies and the digital economy, (2) case studies and examples that illustrate the application of the methodologies and technologies employed, and (3) it is useful for both theoretically and technically oriented researchers.

Chapter 1 lays down the background of digital technologies permeate modern life, affecting everything from the way we work and travel to the way we live and play. Energy digitalization promises to help improve the safety, efficiency, sustainability, and productivity of the global energy system. The digital energy system of the future may be able to identify who needs energy and deliver it to the right place, at the right time, and at the lowest cost. Digitalization is not only improving the flexibility, robustness, and accessibility of energy systems but also raising attention to the security from artificial intelligence (AI)-driven energy, carbon neutrality from energy eco-systems, the transition from the industrial revolutions 4.0 to 5.0, the emerging signs of super smart society 5.0, and so on. This chapter seeks to provide readers with a clearer understanding of what digitalization means for energy—shining a light on both its enormous potential and its most pressing challenges.

Chapter 2 reviews that before the third industrial revolution, humans mainly controlled the operation of energy systems. While currently with the development of energy digitization, big data and AI algorithms are widely applied to control the systems. People are liberated from labor, but the purpose of people orientation should not be ignored. In the fourth industrial revolution in the future, the network of humanities will be revived as the superstructure, forming a new four networks and four flows. This chapter mainly introduces the phenomena, challenge, elements, and foundations of human-centered renaissance from energy digitization.

Chapter 3 discusses the new stage of the sixth information revolution, the concept of four networks and four flows is applied based on the online human–computer interaction networks. This chapter presents an overview of the progression of the information revolution and its amalgamation with the forthcoming Metaverse. Initially, the potential opportunities and challenges associated with the energy revolution are proposed. Subsequently, the transportation transformation during the era of humanistic digital transformation is deliberated upon. Finally, the pivotal role of the human network in intelligent applications is underscored.

Chapter 4 describes that the core of the Four Networks Integration is the integration of the humanistic network under the human–cyber–physical ecosystem. This embodies the top-level design thinking for the development of the digital economy under the background of the new infrastructure, that is, the method of establishing the integrated development of human–cyber–physical systems. This is reflected in the applications of smart energy, smart industry, smart transportation, and smart cities. Specifically, in this chapter, the smart energy system including energy flow and information is discussed; the smart transportation system relying on communications and the exchange of data between different platforms will be investigated; the collaborative robots for industrial IoT in the smart industry system will be explored; and the eco-system operating system for smart city with intelligent computing will be investigated. It is shown that the integration of the humanistic network has become the key to accelerating different intelligent applications.

Chapter 5 shows that data communication between physical entities and virtual entities enables an innovative method for industry to organize the product lifecycle. In addition, the humanistic knowledge and information from the customer side should be brought in, since they play a crucial role in the intelligent industry and smart society. Hence, the data, information, and knowledge interactions among the social, physical, and cyber worlds should be modeled within a dynamic system. With the human–physical–cyber system, intelligence cognition is achieved with the ability to perform prediction, synchronization, and optimization in the digital ecology. This chapter provides the detailed elements and structure of the human–physical–cyber system, as well as the evolution, milestones, and challenges in building it.

Chapter 6 summarizes that the communication of data between physical and virtual entities has revolutionized the way the industry organizes the product lifecycle. By leveraging the power of data, companies can optimize their operations, reduce costs, and improve their products and services. However, data alone is not enough. To achieve true intelligence in the industry and society, it is essential to incorporate humanistic knowledge and customer information. After all, customers are the ultimate arbiters of success in any industry, and their needs and preferences must be considered to achieve sustainable growth. Overall, the human–physical–cyber system represents a powerful tool for achieving intelligence in industry and society. By leveraging the power of data and incorporating humanistic knowledge and customer information, we can build a smarter, more sustainable future for all. Case studies in the following fields are discussed: (1) building new power system with new energy as the main body, (2) smart vehicles and green transportation, (3) smart manufacturing, (4) intelligent integrated energy services and society eco-system, (5) digital renaissance–driven smart city, and (6) practice of integration of four networks four flows with visualization.

The core of far-reaching integration of energy, information, transportation and humanity lies on people-oriented, harmonious coexistence between humans and nature, together with sustainable development, so that both economic development and environment protection are achieved. The basic foundation principle is the deep integration of the humanistic, cyber, and physical worlds. We are excited to be engaged in the endeavors that will have significant impact on the welfare of our future generations.

Chapter one

Challenge and trend on energy digitalization

Wei Han¹, C.C. Chan², Youhao Hu¹, Chang Liu¹ and George You Zhou³,    ¹Sustainable Energy and Environment Thrust, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, P.R. China,    ²The University of Hong Kong, Hong Kong SAR, P.R. China,    ³National Institute of Clean and Low-Carbon Energy, Beijing, P.R. China

Abstract

Digital technologies permeate modern life, affecting everything from the way we work and travel, to the way we live and play. Energy digitalization promises to help improve the safety, efficiency, sustainability, and productivity of the global energy system. The digital energy system of the future may be able to identify who needs energy and deliver it to the right place, at the right time, and at the lowest cost. Digitalization is not only improving the flexibility, robustness, and accessibility of energy systems, but also raising attention to the security from artificial intelligence (AI)–driven energy, carbon neutrality from energy ecosystems, the transition from the industrial revolutions 4.0 to 5.0, the emerging signs of supersmart society 5.0, and so on. This chapter seeks to provide readers with a clearer understanding of what digitalization means for energy—shining a light on both its enormous potential and its most pressing challenges.

Keywords

Energy digitalization; energy security; carbon neutrality; industrial revolution

1.1 Energy security from artificial intelligence–driven energy

1.1.1 The brief review of artificial intelligence

As illustrated in Fig. 1–1, the research in artificial intelligence (AI) has experienced three main stages of development. From the mid-1950s to the 1960s, the first stage presented the AI concept, mainly focusing on machine translation of logical reasoning. The symbolism developed rapidly, and expert systems and knowledge engineering became the research mainstream. After 1960, AI research went through several ups and downs. At this stage, Herbert Simon and Allen Newel developed an automatic theorem-proving system called the Logic Theorist, which was subsequently utilized to prove all theorems in the book Principia Mathematica in less than 2 months. People gradually realized that logical reasoning alone was insufficient to reach the level of machine intelligence. Thus the AI research spontaneously entered the second stage.

Figure 1–1 The process of artificial intelligence (AI) evolution.

From the 1970s to the 1980s, the second stage of AI focused on how to summarize knowledge and then hand over to a computer system for processing. These systems primarily seek to summarize the problem-solving knowledge of human experts, consequently, such knowledge is programmed into computer systems to produce expert systems that can be used to solve real-world problems. Nevertheless, such investigations have been slow to progress due to high development costs. As a result, AI development entered another trough. At this stage, researchers hoped to model and mine the tacit knowledge in the dataset through machine learning (ML) techniques. Hence, the mainstream research of AI stepped to the third stage, namely, the ML Stage, which continues today.

From the 1990s, the third stage of AI started with the objective of solving the bottlenecks in knowledge acquisition by the use of the emerging ML discipline. During this stage, for the first time, IBM’s Deep Blue computer defeated a chess master Garry Kasparov, sparking a wave of AI research. After entering the 21st century, the advances of deep learning (DL) and big data technology brought about a new peak in AI research, called a new generation of AI (AI 2.0). Currently, the hot topic of AI mainly focuses on the theory and method of how to use computers to analyze data, which in turn, can be considered as the theory and methods for intelligent data analysis. Especially in 2006, AI began to enter the cognitive intelligence era emphasizing big data accumulation, theoretical algorithm innovation, computing power improvement, and self-learning. Moreover, AI has made breakthroughs in many application fields, ushering in another AI prosperity. In 2010 and 2011, scholars who had made outstanding contributions to ML were awarded the highest award in computer science, namely, the A.M. Turing Award. In the history of Turing Awards, this extremely rare situation directly reflects the importance of ML in the field of AI. Another milestone of AI 2.0 after 60 years happened in 2016, when Google’s AlphaGo defeated Sedol Lee by 4:1, and almost immediately also defeated Jie Ke, who was ranked first in the world, by a score of 3:0 in May 2017, marking the end of the human machine war [1].

1.1.2 The artificial intelligence in energy systems

The traditional energy system is undergoing a major transformation with the rapid development of renewable energy technologies, which consequently facilitates the huge diversity of energy resources, wide distribution of energy supplies, bidirectional flows of electricity, increased deployment of energy storage, massive streams of data collected by the internet of things (IoT), and the evolving role of utilities and consumers. However, due to the small number of resources that can be controlled automatically, many system-operational decisions are still taken and enacted manually, or with a basic level of automation. Accordingly, the developments of well-integrated AI will allow more automated control resources to respond to the requirements of numerous stakeholders (such as, consumers, generators, transmission and distribution power grids, consumers). AI is applied in almost every type of renewable energy (wind, solar, geothermal, hydro, ocean, biological, hydrogen, and hybrid) for the generation, transmission, distribution, optimization, estimation, management, policy, and so on. This advanced level of control enables optimization of the system with more distributed power plants while maximizing system flexibility and reducing the cost of system operation with high proportions of renewable energies. As a result, the role of AI and big data is evolving from a facilitation and optimization tool to a necessity for intelligent and rapid decision-making [2].

As mentioned earlier, AI and other digital technologies can support the renewable energy sector in a number of ways. Currently, most of the AI-enabled advancements are in advanced weather, renewable energy generation forecasting, and predictive maintenance. In the future, AI as well as big data will further enhance decision-making and planning, condition monitoring and inspecting, supply chain optimization and the general increase of the efficiency of energy systems. The global energy system is currently undergoing a dramatic transformation, and it will continue to become more decentralized, digitized, and decarbonized in the coming decades. In order to meet the commitments made under the 2015 Paris Agreement—limiting the global temperature rise to well below 2°C—this transition must accelerate. Energy systems have become increasingly digitized in recent years, and it is clear that further digitalization will be a key feature of the energy transition and a significant driver of the industry’s progress toward ambitious climate goals. Advancing technology, falling costs, and ubiquitous connectivity are opening the door to new models of energy production and consumption. Digitalization holds the potential to build new architectures of interconnected energy systems, including breaking down traditional boundaries between demand and supply [3]. A simple demonstration of the application framework of AI technology in the energy system is shown in Fig.