Bøger af Lakshmi D

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.

This book presents innovative research works to automate, innovate, design, and deploy AI for Real-World Applications. It discussed AI applications in major cutting-edge technologies and details about deployment solutions for different applications for sustainable development. The application of Blockchain techniques illustrates the ways of optimisation algorithms in this book. The challenges associated with AI deployment are also discussed in detail, and edge computing with machine learning solutions is explained. This book provides multi-domain applications of AI to the readers to help find innovative methods towards the business, sustainability, and customer outreach paradigms in the AI domain.- Focuses on Virtual machine placement and migration techniques for cloud data centres- Presents the role of machine learning and meta-heuristic approaches for optimisation in cloud computing services- Includes application of placement techniques for quality of service, performance, and reliability improvement- Explores data centre resource management, load balancing and orchestration using machine learning techniques- Analyses Dynamic and scalable resource scheduling with a focus on resource managementThe reference work is for postgraduate students, professionals, and academic researchers in computer science and information technology.