Ai Techniques For Renewable Source Integration And Battery Charging Methods In Electric Vehicle Applications
Download Ai Techniques For Renewable Source Integration And Battery Charging Methods In Electric Vehicle Applications PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Ai Techniques For Renewable Source Integration And Battery Charging Methods In Electric Vehicle Applications book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
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.
AI Approaches to Smart and Sustainable Power Systems
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.
Intelligent Engineering Applications and Applied Sciences for Sustainability
Engineering plays a major role in solving real-world problems, from small inconveniences to societal or global concerns around food scarcity, water shortages, environmental damage, problems in housing or infrastructure and more. In today's rapidly evolving world, the development of the latest generation of engineering and technology is crucial for maintaining productivity, innovation, and improving our overall quality of life. Intelligent Engineering Applications and Applied Sciences for Sustainability is an essential research book that serves as a compilation of cutting-edge research and advancements in engineering, science, and technology, and more importantly, how the application of these advancements will guide the path to a more sustainable future. This book focuses on intelligent engineering applications, which encompass the design and implementation of embedded technologies in various domains. It covers a wide range of fields and their influence on the Sustainable Development Goals (SDGs), fostering interdisciplinary approaches and innovative solutions, including additive manufacturing technologies, aerospace science and engineering, agricultural advancements, computer science for sustainable development, applied biosciences, applied mathematics, industrial engineering, robotics and automation, transportation, future mobility, and much more. As an academic, rigorous exploration of various disciplines, this book serves as an invaluable resource for researchers, scholars, and professionals seeking to advance the frontiers of intelligent engineering applications and applied sciences for a sustainable future.