This book introduces the issues and problems that arise when implementing smart energy management for sustainable manufacturing in the automotive manufacturing industry and the analytical tools and applications to deal with them. It uses a number of illustrative examples to explain energy management in automotive manufacturing, which involves most types of manufacturing technology and various levels of energy consumption. It demonstrates how analytical tools can help improve energy management processes, including forecasting, consumption, and performance analysis, emerging new technology identification as well as investment decisions for establishing smart energy consumption practices. It also details practical energy management systems, making it a valuable resource for professionals involved in real energy management processes, and allowing readers to implement the procedures and applications presented.

This book is a contribution from the authors, to share solutions for a better and sustainable power grid. Renewable energy, smart grid security and smart energy management are the main topics discussed in this book.

Smart Energy Grid Engineering provides in-depth detail on the various important engineering challenges of smart energy grid design and operation by focusing on advanced methods and practices for designing different components and their integration within the grid. Governments around the world are investing heavily in smart energy grids to ensure optimum energy use and supply, enable better planning for outage responses and recovery, and facilitate the integration of heterogeneous technologies such as renewable energy systems, electrical vehicle networks, and smart homes around the grid. By looking at case studies and best practices that illustrate how to implement smart energy grid infrastructures and analyze the technical details involved in tackling emerging challenges, this valuable reference considers the important engineering aspects of design and implementation, energy generation, utilization and energy conservation, intelligent control and monitoring data analysis security, and asset integrity. - Includes detailed support to integrate systems for smart grid infrastructures - Features global case studies outlining design components and their integration within the grid - Provides examples and best practices from industry that will assist in the migration to smart grids

This book includes selected papers from the 5th International Conference on Computational Vision and Bio Inspired Computing (ICCVBIC 2021), held in Coimbatore, India, during November 25–26, 2021. This book presents state-of-the-art research innovations in computational vision and bio-inspired techniques. The book reveals the theoretical and practical aspects of bio-inspired computing techniques, like machine learning, sensor-based models, evolutionary optimization and big data modeling and management that make use of effectual computing processes in the bio-inspired systems. It also contributes to the novel research that focuses on developing bio-inspired computing solutions for various domains, such as human–computer interaction, image processing, sensor-based single processing, recommender systems and facial recognition, which play an indispensable part in smart agriculture, smart city, biomedical and business intelligence applications.

This handbook analyzes and develops methods and models to optimize solutions for energy access (for industry and the general world population alike) in terms of reliability and sustainability. With a focus on improving the performance of energy systems, it brings together state-of-the-art research on reliability enhancement, intelligent development, simulation and optimization, as well as sustainable development of energy systems. It helps energy stakeholders and professionals learn the methodologies needed to improve the reliability of energy supply-and-demand systems, achieve more efficient long-term operations, deal with uncertainties in energy systems, and reduce energy emissions. Highlighting novel models and their applications from leading experts in this important area, this book will appeal to researchers, students, and engineers in the various domains of smart energy systems and encourage them to pursue research and development in this exciting and highly relevant field.

This book aims to make the best use of fine-grained smart meter data to process and translate them into actual information and incorporated into consumer behavior modeling and distribution system operations. It begins with an overview of recent developments in smart meter data analytics. Since data management is the basis of further smart meter data analytics and its applications, three issues on data management, i.e., data compression, anomaly detection, and data generation, are subsequently studied. The following works try to model complex consumer behavior. Specific works include load profiling, pattern recognition, personalized price design, socio-demographic information identification, and household behavior coding. On this basis, the book extends consumer behavior in spatial and temporal scale. Works such as consumer aggregation, individual load forecasting, and aggregated load forecasting are introduced. We hope this book can inspire readers to define new problems, apply novel methods, and obtain interesting results with massive smart meter data or even other monitoring data in the power systems.

"This reference book covers the latest innovations and trends within smart grid and microgrid development, detailing benefits, challenges, and opportunities, that will help readers to fully understand the current opportunities that smart grids and microgrids present around the world"--