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.

The principal advantage of smart electricity meters is their ability to transfer digitized electricity consumption data to remote processing systems. The data collected by these devices make the realization of many novel use cases possible, providing benefits to electricity providers and customers alike. This book includes 14 research articles that explore and exploit the information content of smart meter data, and provides insights into the realization of new digital solutions and services that support the transition towards a sustainable energy system. This volume has been edited by Andreas Reinhardt, head of the Energy Informatics research group at Technische Universität Clausthal, Germany, and Lucas Pereira, research fellow at Técnico Lisboa, Portugal.

Experts in data analytics and power engineering present techniques addressing the needs of modern power systems, covering theory and applications related to power system reliability, efficiency, and security. With topics spanning large-scale and distributed optimization, statistical learning, big data analytics, graph theory, and game theory, this is an essential resource for graduate students and researchers in academia and industry with backgrounds in power systems engineering, applied mathematics, and computer science.

Discusses concepts of smart grid technologies, from the perspective of integration with cloud computing and data management approaches.

Information and communication technologies play an essential role in the effectiveness and efficiency of smart city processes. Recognizing the role of process analysis in energy usage and how it can be enhanced is essential to improving city sustainability. Smart Grid Analytics for Sustainability and Urbanization provides emerging research on the development of information technology and communication systems in smart cities and smart grids. While highlighting topics such as process mining, innovation management, and sustainability optimization, this publication explores technology development and the mobilization of different environments in smart cities. This book is an important resource for graduate students, researchers, academics, engineers, and government officials seeking current research on how process analysis in energy usage is manifested and how it can be enhanced.

A comprehensive data analytics program is the only way utilities will be able to meet the challenges of modern grids with operational efficiency, while reconciling the demands of greenhouse gas legislation, and establishing a meaningful return on investment from smart grid deployments. This book addresses the requirements for applying big data technologies and approaches, including Big Data cybersecurity, to the critical infrastructure that makes up the electrical utility grid.

By implementing a comprehensive data analytics program, utility companies can meet the continually evolving challenges of modern grids that are operationally efficient, while reconciling the demands of greenhouse gas legislation and establishing a meaningful return on investment from smart grid deployments. Readable and accessible, Big Data Analytics Strategies for the Smart Grid addresses the needs of applying big data technologies and approaches, including Big Data cybersecurity, to the critical infrastructure that makes up the electrical utility grid. It supplies industry stakeholders with an in-depth understanding of the engineering, business, and customer domains within the power delivery market. The book explores the unique needs of electrical utility grids, including operational technology, IT, storage, processing, and how to transform grid assets for the benefit of both the utility business and energy consumers. It not only provides specific examples that illustrate how analytics work and how they are best applied, but also describes how to avoid potential problems and pitfalls. Discussing security and data privacy, it explores the role of the utility in protecting their customers’ right to privacy while still engaging in forward-looking business practices. The book includes discussions of: SAS for asset management tools The AutoGrid approach to commercial analytics Space-Time Insight’s work at the California ISO (CAISO) This book is an ideal resource for mid- to upper-level utility executives who need to understand the business value of smart grid data analytics. It explains critical concepts in a manner that will better position executives to make the right decisions about building their analytics programs. At the same time, the book provides sufficient technical depth that it is useful for data analytics professionals who need to better understand the nuances of the engineering and business challenges unique to the utilities industry.

This book introduces big data analytics and corresponding applications in smart grids. The characterizations of big data, smart grids as well as a huge amount of data collection are first discussed as a prelude to illustrating the motivation and potential advantages of implementing advanced data analytics in smart grids. Basic concepts and the procedures of typical data analytics for general problems are also discussed. The advanced applications of different data analytics in smart grids are addressed as the main part of this book. By dealing with a huge amount of data from electricity networks, meteorological information system, geographical information system, etc., many benefits can be brought to the existing power system and improve customer service as well as social welfare in the era of big data. However, to advance the applications of big data analytics in real smart grids, many issues such as techniques, awareness, and synergies have to be overcome. This book provides deployment of semantic technologies in data analysis along with the latest applications across the field such as smart grids.