Ai Techniques For Renewable Source Integration And Battery Charging Methods In Electric Vehicle Applications

Artificial intelligence techniques applied in the power system sector make the prediction of renewable power source generation and demand more efficient and effective. Additionally, since renewable sources are intermittent in nature, it is necessary to predict and analyze the data of input sources. Hence, further study on the prediction and data analysis of renewable energy sources for sustainable development is required. AI Techniques for Renewable Source Integration and Battery Charging Methods in Electric Vehicle Applications focuses on artificial intelligence techniques for the evolving power system field, electric vehicle market, energy storage elements, and renewable energy source integration as distributed generators. Covering key topics such as deep learning, artificial intelligence, and smart solar energy, this premier reference source is ideal for environmentalists, computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.

In today’s modern society, to reduce the carbon dioxide gas emission from motor vehicles and to save mother nature, electric vehicles are becoming more practical. As more people begin to see the benefits of this technology, further study on the challenges and best practices is required. Artificial Intelligence Applications in 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 premier reference source is ideal for government officials, industry professionals, policymakers, researchers, scholars, practitioners, academicians, instructors, and students.

This book presents the latest research on applications of artificial intelligence and the Internet of Things in renewable energy systems. Advanced renewable energy systems must necessarily involve the latest technology like artificial intelligence and Internet of Things to develop low cost, smart and efficient solutions. Intelligence allows the system to optimize the power, thereby making it a power efficient system; whereas, Internet of Things makes the system independent of wire and flexibility in operation. As a result, intelligent and IOT paradigms are finding increasing applications in the study of renewable energy systems. This book presents advanced applications of artificial intelligence and the internet of things in renewable energy systems development. It covers such topics as solar energy systems, electric vehicles etc. In all these areas applications of artificial intelligence methods such as artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above, called hybrid systems, are included. The book is intended for a wide audience ranging from the undergraduate level up to the research academic and industrial communities engaged in the study and performance prediction of renewable energy systems.

The increase in air pollution and vehicular emissions has led to the development of the renewable energy-based generation and electrification of transportation. Further, the electrification shift faces an enormous challenge due to limited driving range, long charging time, and high initial cost of deployment. Firstly, there has been a discussion on renewable energy such as how wind power and solar power can be generated by wind turbines and photovoltaics, respectively, while these are intermittent in nature. The combination of these renewable energy resources with available power generation system will make electric vehicle (EV) charging sustainable and viable after the payback period. Recently, there has also been a significant discussion focused on various EV charging types and the level of power for charging to minimize the charging time. By focusing on both sustainable and renewable energy, as well as charging infrastructures and technologies, the future for EV can be explored. Developing Charging Infrastructure and Technologies for Electric Vehicles reviews and discusses the state of the art in electric vehicle charging technologies, their applications, economic, environmental, and social impact, and integration with renewable energy. This book captures the state of the art in electric vehicle charging infrastructure deployment, their applications, architectures, and relevant technologies. In addition, this book identifies potential research directions and technologies that facilitate insights on EV charging in various charging places such as smart home charging, parking EV charging, and charging stations. This book will be essential for power system architects, mechanics, electrical engineers, practitioners, developers, practitioners, researchers, academicians, and students interested in the problems and solutions to the state-of-the-art status of electric vehicles.

Today, the global power demand relies on a delicate balance between conventional and renewable energy systems, necessitating both efficient power generation and the effective utilization of these energy resources through appropriate energy storage solutions. Integrating microgrid systems into the utility grid has become a critical facet of modern power systems. The intermittent and unpredictable nature of these energy sources poses a formidable challenge for academic scholars and researchers. This compels them to explore under-investigated areas, including energy source estimation, storage elements, load pattern prediction, coordination among distributed sources, and the development of energy management algorithms for precise and efficient control. AI Approaches to Smart and Sustainable Power Systems tackles these issues using cutting-edge AI techniques. It examines the most effective methods to optimize voltage, frequency, power, fault diagnosis, component health, and overall power system quality and reliability. AI empowers predictive and preventive maintenance for a sustainable energy future. The book focuses on emerging research areas, including renewable energy, power flow calculations, demand scheduling, real-time performance validation, and AI integration into modern power systems, accompanied by insightful case studies.

This book focuses on the latest emerging technologies in electric vehicles (EV), and their economic and environmental impact. The topics covered include different types of EV such as hybrid electrical vehicle (HEV), battery electrical vehicle (BEV), fuel cell electrical vehicle (FCEV), plug-in hybrid electrical vehicle (PHEV). Theoretical background and practical examples of conventional electrical machines, advanced electrical machines, battery energy sources, on-board charging and off-board charging techniques, and optimization methods are presented here. This book can be useful for students, researchers and practitioners interested in different problems and challenges associated with electric vehicles.

Electric Vehicle Integration in a Smart Microgrid Environment The growing demand for energy in today’s world, especially in the Middle East and Southeast Asia, has been met with massive exploitation of fossil fuels, resulting in an increase in environmental pollutants. In order to mitigate the issues arising from conventional internal combustion engine-powered vehicles, there has been a considerable acceleration in the adoption of electric vehicles (EVs). Research has shown that the impact of fossil fuel use in transportation and surging demand in power owing to the growing EV charging infrastructure can potentially be minimalized by smart microgrids. As EVs find wider acceptance with major advancements in high efficiency drivetrain and vehicle design, it has become clear that there is a need for a system-level understanding of energy storage and management in a microgrid environment. Practical issues, such as fleet management, coordinated operation, repurposing of batteries, and environmental impact of recycling and disposal, need to be carefully studied in the context of an ageing grid infrastructure. This book explores such a perspective with contributions from leading experts on planning, analysis, optimization, and management of electrified transportation and the transportation infrastructure. The primary purpose of this book is to capture state-of-the-art development in smart microgrid management with EV integration and their applications. It also aims to identify potential research directions and technologies that will facilitate insight generation in various domains, from smart homes to smart cities, and within industry, business, and consumer applications. We expect the book to serve as a reference for a larger audience, including power system architects, practitioners, developers, new researchers, and graduate-level students, especially for emerging clean energy and transportation electrification sectors in the Middle East and Southeast Asia.

Electric Vehicle Integration into Modern Power Networks provides coverage of the challenges and opportunities posed by the progressive integration of electric drive vehicles. Starting with a thorough overview of the current electric vehicle and battery state-of-the-art, this work describes dynamic software tools to assess the impacts resulting from the electric vehicles deployment on the steady state and dynamic operation of electricity grids, identifies strategies to mitigate them and the possibility to support simultaneously large-scale integration of renewable energy sources. New business models and control management architectures, as well as the communication infrastructure required to integrate electric vehicles as active demand are presented. Finally, regulatory issues of integrating electric vehicles into modern power systems are addressed. Inspired by two courses held under the EES-UETP umbrella in 2010 and 2011, this contributed volume consists of nine chapters written by leading researchers and professionals from the industry as well as academia.