A Sustainable Future With E Mobility Concepts Challenges And Implementations
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A Sustainable Future with E-Mobility: Concepts, Challenges, and Implementations
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.
Neural Networks and Graph Models for Traffic and Energy Systems
Neural networks and graph models play a transformative role in optimizing traffic and energy systems, offering advanced solutions for managing complex, interconnected infrastructures. Neural networks can predict traffic patterns, optimize routes, and improve the efficiency of energy distribution networks by learning from real-time data. Graph models help represent and analyze the relationships and flows within transportation and energy systems, enabling more accurate modeling of networks and their interactions. Together, these technologies allow for smarter traffic management, reduced congestion, and enhanced energy grid efficiency. As cities and industries continue to grow, integrating neural networks and graph models into traffic and energy systems is essential in creating sustainable, efficient, and resilient urban environments. Neural Networks and Graph Models for Traffic and Energy Systems explores the sophisticated techniques and practical uses of artificial intelligence in improving and overseeing traffic and energy networks. It examines the connection between neural networks and graph theory, showing how these technologies might transform the effectiveness, sustainability, and robustness of urban infrastructure. This book covers topics such as sustainable development, energy science, traffic systems, and is a useful resource for energy scientists, computer engineers, urban developers, academicians, and researchers.
Convergence of AI, Education, and Business for Sustainability
The convergence of artificial intelligence (AI), education, and business presents an opportunity to drive sustainability across industries and societies. As the world faces complex environmental, social, and economic challenges, AI offers innovative solutions to optimize resource usage, streamline business operations, and enhance decision-making processes for sustainable outcomes. In education, AI enables personalized learning experiences, equipping future generations with the knowledge and skills needed to tackle sustainability challenges. Businesses adopt AI to innovate sustainable products and services, reduce carbon footprints, and create a circular economy. This intersection between AI, education, and business reshapes how sustainability is approached while creating a new framework for collaboration, where technology, learning, and commerce work in harmony to build a more sustainable and equitable future. Convergence of AI, Education, and Business for Sustainability explores successful, scalable, and replicable AI applications that contribute to sustainability goals. It bridges the gap between theoretical AI advancements and practical sustainability solutions, encouraging further innovation, investment, and interdisciplinary research in this critical area. This book covers topics such as environmental science, green business, and human resources, and is a useful resource for environmentalists, business owners, educators, academicians, computer engineers, data scientists, and researchers.