Future Modern Distribution Networks Resilience
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Future Modern Distribution Networks Resilience
Author: Seyed Mohammad Taghi Gharibzahedi
language: en
Publisher: Elsevier
Release Date: 2024-02-23
Future Modern Distribution Networks Resilience examines the combined impact of low-probability and high-impact events on modern distribution systems' resilience. Using practical guidance, the book provides comprehensive approaches for improving energy systems' resilience by utilizing infrastructure and operational strategies. Divided in three parts, Part One provides a conceptual introduction and review of power system resilience, including topics such as risk and vulnerability assessment in power systems, resilience metrics, and power systems operation and planning. Part Two discusses modelling of vulnerability and resilience evaluation indices and cost-benefit analysis. Part Three reviews infrastructure and operational strategies to improve power system resilience, including robust grid hardening strategies, mobile energy storage and electric vehicles, and networked microgrids and renewable energy resources. With a strong focus on economic results and cost-effectives, Future Modern Distribution Networks Resilience is a practical reference for students, researchers and engineers interested in power engineering, energy systems, and renewable energy. - Reviews related concepts to active distribution systems resilience before, during, and after a sudden disaster - Presents analysis of risk and vulnerability for reliable evaluation, sustainable operation, and accurate planning of energy grids against low-probability and high-impact events - Highlights applications of practical metrics for resilience assessment of future energy networks - Provides guidance for the development of cost-effective resilient techniques for reducing the vulnerability of electrical grids to severe disasters
Methodologies, Frameworks, and Applications of Machine Learning
Author: Srivastava, Pramod Kumar
language: en
Publisher: IGI Global
Release Date: 2024-03-22
Technology is constantly evolving, and machine learning is positioned to become a pivotal tool with the power to transform industries and revolutionize everyday life. This book underscores the urgency of leveraging the latest machine learning methodologies and theoretical advancements, all while harnessing a wealth of realistic data and affordable computational resources. Machine learning is no longer confined to theoretical domains; it is now a vital component in healthcare, manufacturing, education, finance, law enforcement, and marketing, ushering in an era of data-driven decision-making. Academic scholars seeking to unlock the potential of machine learning in the context of Industry 5.0 and advanced IoT applications will find that the groundbreaking book, Methodologies, Frameworks, and Applications of Machine Learning, introduces an unmissable opportunity to delve into the forefront of modern research and application. This book offers a wealth of knowledge and practical insights across a wide array of topics, ranging from conceptual frameworks and methodological approaches to the application of probability theory, statistical techniques, and machine learning in domains as diverse as e-government, healthcare, cyber-physical systems, and sustainable development, this comprehensive guide equips you with the tools to navigate the complexities of Industry 5.0 and the Internet of Things (IoT).
Enhancing Resilience in Power Distribution Systems
Enhancing Resilience in Power Distribution Systems presents practical guidance for readers on the challenges and potential solutions for resilience in modern power systems. The book begins by explaining the risks and problems for resilience presented by renewable-based power systems. It goes on to clarify the current state of research and propose several novel methodologies and technologies for analysis and improvement of power system resilience. These methods include deep learning, linear programming, and generative adversarial networks.Packed with practical steps and tools for implementing the latest technologies, this book provides researchers and industry professionals with guidance on the resilient systems of the future. - Breaks down novel methodologies and tools from deep learning to generative adversarial networks - Supports readers in implementing practical steps towards resilient renewable energy - Presents practical guidance for readers on the challenges and potential solutions for resilience in modern power systems