Anita Sardana – författare

The application of artificial intelligence (AI) to the management and development of renewable energy sources has revolutionized the energy sector by enhancing efficiency, reliability, and scalability. With the capability to analyze weather patterns, solar radiation, and wind speeds, AI-driven technologies help ensure optimal utilization of such resources as solar panels and wind turbines. They also enable precise forecasting of energy production. Additionally, AI-powered systems can facilitate real-time monitoring and predictive maintenance of renewable energy infrastructure to reduce downtime and operational costs. With AI, the renewable energy industry can overcome challenges, maximize output, and contribute significantly to global efforts in combating climate change.Artificial Intelligence for Renewable Energy Systems focuses on using AI technology to advance green energy and its management. Starting with an overview of applying AI to renewable energy management, the book follows with such real-world as:Predictive analytics for wind turbine maintenanceIntelligent solar grid integrationVehicle-to-grid (V2G) technology for electric mobilityIntelligent hydrogen fuel cell control.It also features global trend research, methods for data-driven forecasting, and policymaking based on advanced data analytics and visualization.Taking a multidisciplinary approach, the book is a guide for academics, energy practitioners, engineers, and policymakers who are leveraging the constructive collaboration between AI and renewable energy technologies.

SIMULATION TECHNIQUES OF DIGITAL TWIN IN REAL-TIME APPLICATIONS The book gives a complete overview of implementing digital twin technology in real-time scenarios while emphasizing how this technology can be embedded with running technologies to solve all other issues. Divided into two parts with Part 1 focusing on simulated techniques in digital twin technology and Part 2 on real-time applications of digital twin technology, the book collects a significant number of important research articles from domain-specific experts. The book sheds light on the various techniques of digital twin technology that are implemented in various application areas. It emphasizes error findings and respective solutions before the actual event happens. Most of the features in the book are on the implementation of strategies in real-time applications. Various real-life experiences are taken to show the proper implementation of simulation technologies. The book shows how engineers of any technology can input their research ideas to convert to real scenarios by using replicas. Hence, the book has a collection of research articles from various engineers with expertise in different technologies from many regions of the world. It shows how to implement the embedded real-time data into technologies. Specifically, the chapters relate to the auto landing and cruising features in aerial vehicles, automated coal mining simulation strategy, the enhancement of workshop equipment, and implementation in power energy management for urban railways. This book also describes the coherent mechanism of digital twin technologies with deep neural networks and artificial intelligence. Audience Researchers, engineers, and students in computer science, software engineering and industrial engineering, will find this book to be very useful.