The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. This book, which constitutes the eighth volume of the Transactions on Rough Sets series, contains a wide spectrum of contributions to the theory and applications of rough sets. The 17 papers presented explore several research streams and introduce a number of new advances in the foundations and applications of artificial intelligence, engineering, logic, mathematics, and science.
Converter-Based Dynamics and Control of Modern Power Systems addresses the ongoing changes and challenges in rotating masses of synchronous generators, which are transforming dynamics of the electrical system. These changes make it more important to consider and understand the role of power electronic systems and their characteristics in shaping the subtleties of the grid and this book fills that knowledge gap. Balancing theory, discussion, diagrams, mathematics, and data, this reference provides the information needed to acquire a thorough overview of resilience issues and frequency definition and estimation in modern power systems. This book offers an overview of classical power system dynamics and identifies ways of establishing future challenges and how they can be considered at a global level to overcome potential problems. The book is designed to prepare future engineers for operating a system that will be driven by electronics and less by electromechanical systems. - Includes theory on the emerging topic of electrical grids based on power electronics - Creates a good bridge between traditional theory and modern theory to support researchers and engineers - Links the two fields of power systems and power electronics in electrical engineering
`Electric energy must be treated as a commodity which can be bought, sold, and traded, taking into account its time- and space-varying values and costs.` Spot Pricing of Electricity, Schweppe et al, 1988. Computational Auction Mechanisms for Restructured Power Industry Operation outlines the application of auction methods for all aspects of power system operation, primarily for a competitive environment. A complete description of the industry structure as well as the various markets now being formed is given. A thorough introduction to auction basics is included to explain how auctions have grown in other industries. Auction methods are compared to classical techniques for power system analysis, operations, and planning. The traditional applications of economic dispatch, optimal power flow and unit commitment are compared to auction mechanisms. Algorithms for auctions using linearized power flow equations, DC power flow equations, and AC power flow equations are included. The bundling of supportive services, known as ancillary services within the United States, is discussed. Extensions to the basic auction algorithms for inclusion of supportive services as well as algorithms for scheduling and bidding on generation for GENCOs or independent power producers are presented. Algorithms for scheduling and contracting with customers are also presented for energy service companies. An introduction to the various commodity and financial market products includes the use of futures and options for GENCOs. The material is useful for students performing research on the new business environment based on competition. Regulators will find information on initial methods of designing and evaluating market systems, and power exchange and financial analysts will find information on the interdependence of markets and power system-based techniques for risk management. This information compares the new business environment solutions with old business environment solutions. Computational Auction Mechanisms for Restructured Power Industry Operation provides a first introduction to how electricity will be traded as a commodity in the future.
Dynamic management of systems development is a precondition for the realization of sustainable system development. This approach allows for the usage of systems theory methods that take into consideration the interaction of decisions made over time and space. A characteristic feature of this kind of method is that the process of sophisticated object development over time is examined for optimal decision selection. This requires the application of modelling methods that represent properties of the developing objects, high speed calculation methods for the estimation of technical and economic characteristics, as well as effective optimization methods. Dynamic Management of Sustainable Development presents a concise summary of the authors’ research in the area of dynamic methods analysis of technical systems development. Along with systematic illustration of mathematical methods, considerable attention is drawn to practical realization and applications. Dynamic Management of Sustainable Development will be helpful for scientists involved in the mathematical modelling of large technical systems development and for engineers working in the area of large technical systems planning.
This book evaluates the role of innovative machine learning and deep learning methods in dealing with power system issues, concentrating on recent developments and advances that improve planning, operation, and control of power systems. Cutting-edge case studies from around the world consider prediction, classification, clustering, and fault/event detection in power systems, providing effective and promising solutions for many novel challenges faced by power system operators. Written by leading experts, the book will be an ideal resource for researchers and engineers working in the electrical power engineering and power system planning communities, as well as students in advanced graduate-level courses.
Big Data Application in Power Systems, Second Edition presents a thorough update of the previous volume, providing readers with step-by-step guidance in big data analytics utilization for power system diagnostics, operation, and control. Bringing back a team of global experts and drawing on fresh, emerging perspectives, this book provides cutting-edge advice for meeting today's challenges in this rapidly accelerating area of power engineering. Divided into three parts, this book begins by breaking down the big picture for electric utilities, before zooming in to examine theoretical problems and solutions in detail. Finally, the third section provides case studies and applications, demonstrating solution troubleshooting and design from a variety of perspectives and for a range of technologies. Readers will develop new strategies and techniques for leveraging data towards real-world outcomes. Including five brand new chapters on emerging technological solutions, Big Data Application in Power Systems, Second Edition remains an essential resource for the reader aiming to utilize the potential of big data in the power systems of the future. - Provides a total refresh to include the most up-to-date research, developments, and challenges - Focuses on practical techniques, including rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches for processing high dimensional, heterogeneous, and spatiotemporal data - Engages with cross-disciplinary lessons, drawing on the impact of intersectional technology including statistics, computer science, and bioinformatics - Includes five brand new chapters on hot topics, ranging from uncertainty decision-making to features, selection methods, and the opportunities provided by social network data