Artificial Intelligence-Empowered Modern Electric Vehicles in Smart Grid Systems: Fundamentals, Technologies, and Solutions is an essential reference for energy researchers, graduate students and engineers who aim to understand the opportunities offered by artificial intelligence for the integration of electric vehicles into smart grids. This book begins by building foundational knowledge for the reader, covering the essentials of artificial intelligence and its applications for electric vehicles in a clear and holistic manner. Next, it breaks down two essential areas of application in more detail: energy management (from to energy harvesting to demand response and complex forecasting), and market strategies (including peer-to-peer, vehicle-to-vehicle, and vehicle-to-everything trading, plus the cyber-security implications). A final part provides detailed case studies and close consideration of challenges, including code and data sets for replication of techniques. Providing a clear pathway from fundamentals to practical implementation, Artificial Intelligence-Empowered Modern Electric Vehicles in Smart Grid Systems will provide multidisciplinary guidance for implementing this cutting-edge technology in the energy systems of the future. - Supports fundamental understanding of artificial intelligence and its opportunities for energy system specialists - Collects the real-world experiences of global experts - Enables practical implementation of artificial intelligence strategies that support renewable energy integration across energy systems, markets, and grids

As more and more communities around the world are turning to electric vehicles (EVs) to help the environment and save energy, we face a big challenge. The systems that deliver power to our homes and businesses are having a tough time keeping up, especially with the increasing use of EVs. This challenge is a major issue for the experts in the energy field who are working hard to figure out how to make sure our power systems stay reliable. The main goal for these experts right now is to create a strong, flexible system that can smoothly handle the integration of EVs, making sure the power flows well, the grid stays stable, and the systems remain eco-friendly. E-Mobility in Electrical Energy Systems for Sustainability is a comprehensive guide to navigating the complexities of e-mobility integration. Delving into crucial aspects such as architectural reconfiguration, restoration strategies, power quality control, and regulatory frameworks, the book provides solutions on how to address the challenges posed by the integration of EVs into distribution systems. Its examination of advanced technologies, including communication-enabled EV charging systems, battery management systems, and power grid cybersecurity measures, equips readers with the knowledge needed to start the transformative journey towards sustainable electric transportation. This book is a great resource for those seeking to understand, engage with, and contribute to the landscape of e-mobility integration.

Integrating electric vehicles (EVs) into power distribution systems presents significant challenges, particularly concerning power source dependability and grid stability. The distribution system, a critical element of the power system, is susceptible to failures and power outages exacerbated by the extensive adoption of EVs. Additionally, managing the administration, monitoring, and control of power systems in the context of EV integration is a complex and daunting task for energy experts. A Sustainable Future with E-Mobility: Concepts, Challenges, and Implementations offers a comprehensive solution to these challenges. It explores infrastructure frameworks, planning strategies, control strategies, and software applications for integrating EVs with power distribution systems, focusing on innovative grid developments. By providing insights into architectural reconfiguration, restoration strategies, power quality control, and regulatory aspects, the book equips students, researchers, academicians, policymakers, and industry experts with the knowledge needed to achieve a secure, resilient, and efficient integration of EVs into distribution networks.

Cyber-physical systems (CPS) are "engineered systems that are built from, and depend upon, the seamless integration of computational algorithms and physical components." CPS can be small and closed, such as an artificial pancreas, or very large, complex, and interconnected, such as a regional energy grid. CPS engineering focuses on managing inter- dependencies and impact of physical aspects on cyber aspects, and vice versa. With the development of low-cost sensing, powerful embedded system hardware, and widely deployed communication networks, the reliance on CPS for system functionality has dramatically increased. These technical developments in combination with the creation of a workforce skilled in engineering CPS will allow the deployment of increasingly capable, adaptable, and trustworthy systems. Engineers responsible for developing CPS but lacking the appropriate education or training may not fully understand at an appropriate depth, on the one hand, the technical issues associated with the CPS software and hardware or, on the other hand, techniques for physical system modeling, energy and power, actuation, signal processing, and control. In addition, these engineers may be designing and implementing life-critical systems without appropriate formal training in CPS methods needed for verification and to assure safety, reliability, and security. A workforce with the appropriate education, training, and skills will be better positioned to create and manage the next generation of CPS solutions. A 21st Century Cyber-Physical Systems Education examines the intellectual content of the emerging field of CPS and its implications for engineering and computer science education. This report is intended to inform those who might support efforts to develop curricula and materials; faculty and university administrators; industries with needs for CPS workers; and current and potential students about intellectual foundations, workforce requirements, employment opportunities, and curricular needs.

Smart grid technologies include sensing and measurement technologies, advanced components aided with communications and control methods along with improved interfaces and decision support systems. Smart grid techniques support the extensive inclusion of clean renewable generation in power systems. Smart grid use also promotes energy saving in power systems. Cyber security objectives for the smart grid are availability, integrity and confidentiality. Five salient features of this book are as follows: AI and IoT in improving resilience of smart energy infrastructure IoT, smart grids and renewable energy: an economic approach AI and ML towards sustainable solar energy Electrical vehicles and smart grid Intelligent condition monitoring for solar and wind energy systems

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

AI-Powered IoT in the Energy Industry: Digital Technology and Sustainable Energy Systems looks at opportunities to employ cutting-edge applications of artificial intelligence (AI), the Internet of Things (IoT), and Machine Learning (ML) in designing and modeling energy and renewable energy systems. The book's main objectives are to demonstrate how big data can help with energy efficiency and demand reduction, increase the usage of renewable energy sources, and assist in transitioning from a centralized system to a distributed, efficient, and embedded energy system. Contributions cover the fundamentals of the renewable energy sector, including solar, wind, biomass, and hydrogen, as well as building services and power generation systems. Chapters also examine renewable energy property prediction methods and discuss AI and IoT prediction models for biomass thermal properties. ​Covers renewable energy sector fundamentals; Explains the application of big data in distributed energy domains; Discusses AI and IoT prediction methods and models.

"The Handbook of Research on Battery Management Systems and Routing Problems in Electric Vehicles focuses on the integration of renewable energy sources with the existing grid, introduces a power exchange scenario in the prevailing power market, considers the use of the electric vehicle market for creating cleaner and transformative energy, and optimizes the control variables with artificial intelligence techniques. Covering key topics such as artificial intelligence, smart grids, and sustainable development, this major reference work is ideal for government officials, industry professionals, policymakers, researchers, scholars, practitioners, academicians, instructors, and students"--

In the era of propelling traditional energy systems to evolve towards smart energy systems, including power generation, energy storage systems, and electricity consumption have become more dynamic. The quality and reliability of power supply are impacted by the sporadic and rising use of electric vehicles, domestic loads, and industrial loads. Similarly, with the integration of solid state devices, renewable sources, and distributed generation, power generation processes are evolving in a variety of ways. Several cutting-edge technologies are necessary for the safe and secure operation of power systems in such a dynamic setting, including load distribution, automation, energy regulation & control, and energy trading. This book covers the applications of various big data analytics,artificial intelligence, and machine learning technologies in smart grids for demand prediction, decision-making processes, policy, and energy management. The book delves into the new technologies for modern power systems such as the Internet of Things, Blockchain for smart home and smart city solutions in depth. Technical topics discussed in the book include: • Hybrid smart energy system technologies • Smart meters • Energy demand forecasting • Use of different protocols and communication in smart energy systems • Power quality and allied issues and mitigation using AI • Intelligent transportation • Virtual power plants • AI based smart energy business models • Smart home solutions • Blockchain solutions for smart grids.