Energy storage is one of the most important enablers for the transformation to a sustainable energy supply with greater mobility. For vehicles, but also for many stationary applications, the batteries used for energy storage are very flexible but also have a rather limited lifetime compared to other storage principles. This Special Issue is a collection of articles that collectively address the following questions: What are the factors influencing the aging of different energy storage technologies? How can we extend the lifetime of storage systems? How can the aging of an energy storage be detected and predicted? When do we have to exchange the storage device? The articles cover lithium-ion batteries, supercaps, and flywheels.
This handbook serves as a guide to deploying battery energy storage technologies, specifically for distributed energy resources and flexibility resources. Battery energy storage technology is the most promising, rapidly developed technology as it provides higher efficiency and ease of control. With energy transition through decarbonization and decentralization, energy storage plays a significant role to enhance grid efficiency by alleviating volatility from demand and supply. Energy storage also contributes to the grid integration of renewable energy and promotion of microgrid.
Battery System Modeling provides advances on the modeling of lithium-ion batteries. Offering step-by-step explanations, the book systematically guides the reader through the modeling of state of charge estimation, energy prediction, power evaluation, health estimation, and active control strategies. Using applications alongside practical case studies, each chapter shows the reader how to use the modeling tools provided. Moreover, the chemistry and characteristics are described in detail, with algorithms provided in every chapter. Providing a technical reference on the design and application of Li-ion battery management systems, this book is an ideal reference for researchers involved in batteries and energy storage. Moreover, the step-by-step guidance and comprehensive introduction to the topic makes it accessible to audiences of all levels, from experienced engineers to graduates. - Explains how to model battery systems, including equivalent, electrical circuit and electrochemical nernst modeling - Includes comprehensive coverage of battery state estimation methods, including state of charge estimation, energy prediction, power evaluation and health estimation - Provides a dedicated chapter on active control strategies
Electrochemical energy storage is a key element of systems in a wide range of sectors, such as electro-mobility, portable devices, and renewable energy. The energy storage systems (ESSs) considered here are batteries, supercapacitors, and hybrid components such as lithium-ion capacitors. The durability of ESSs determines the total cost of ownership, the global impacts (lifecycle) on a large portion of these applications and, thus, their viability. Understanding ESS aging is a key to optimizing their design and usability in terms of their intended applications. Knowledge of ESS aging is also essential to improve their dependability (reliability, availability, maintainability, and safety). This Special Issue includes 12 research papers and 1 review article focusing on battery, supercapacitor, and hybrid capacitor aging.
Energy storage will be a very important part of the near future, and its effectiveness will be crucial for most future technologies. Energy can be stored in several different ways and these differ in terms of the type and the conversion method of the energy. Among those methods; chemical, mechanical, and thermal energy storage are some of the most favorable methods for containing energy. Current energy storage devices are still far from meeting the demands of new technological developments. Therefore, much effort has been put to improving the performance of different types of energy storage technologies in the last few decades.
A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed. Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and several approximation methods for learning with large datasets are discussed. The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes.
In this comprehensive guide for practicing engineers and students, Ertugrul explains the field of renewable energy and distributed generation technologies and describes the transformation occurring in power grids due to the rise of renewable energy sources and emerging technologies. This book covers key areas such as the status of grid transformation, photovoltaic (PV) solar energy, wind energy systems, distributed energy resources, microgrids, grid‐scale and domestic battery storage systems, e‐mobility and emerging distributed energy technologies. The text presents an equilibrium between theoretical concepts and practical applications, with each chapter emphasizing both theory and practical application. Each chapter commences with a lucid explanation of the subject matter, which is then succeeded by an investigation into its real‐world applications and implications. Supplementary material is also provided, such as real wind data files, PV data files and Matrix Laboratory (MATLAB®) and Excel codes. This includes a sample real data set from grid‐scale autonomous microgrid test platforms and household, distribution and transmission‐level power system data. The book also incorporates a section consisting of problems, quizzes and solutions. This element prompts the reader to put the theoretical knowledge to use in addressing real‐world challenges, thereby cultivating a more in‐depth grasp of the topic. Through this in‐depth approach, readers will be able to apply their comprehensive knowledge and practical understanding to decision‐making regarding future challenges in the energy industry. This book is an invaluable guide for professionals working in the field, particularly those who aim to stay updated on the latest technologies and trends. Undergraduate and postgraduate students will also benefit from the book’s comprehensive approach and inclusion of real‐world data and problems to solve, which will build their expertise and give them a solid foundation for their future careers.
The three-volume set CCIS 1467, CCIS 1468, and CCIS 1469 constitutes the thoroughly refereed proceedings of the 7th International Conference on Life System Modeling and Simulation, LSMS 2021, and of the 7th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2021, held in Hangzhou, China, in October 2021. The 159 revised papers presented were carefully reviewed and selected from over 430 submissions. The papers of this volume are organized in topical sections on: Medical Imaging and Analysis Using Intelligence Computing; Biomedical signal processing, imaging, visualization and surgical robotics; Computational method in taxonomy study and neural dynamics; Intelligent medical apparatus, clinical applications and intelligent design of biochips; Power and Energy Systems; Computational Intelligence in Utilization of Clean and Renewable Energy Resources, and Intelligent Modelling, Control and Supervision for Energy Saving and Pollution Reduction; Intelligent Methods in Developing Electric Vehicles, Engines and Equipment; Intelligent Control Methods in Energy Infrastructure Development and Distributed Power Generation Systems; Intelligent Modeling, Simulation and Control of Power Electronics and Power Networks; Intelligent Techniques for Sustainable Energy and Green Built Environment, Water Treatment and Waste Management; Intelligent Robot and Simulation; Intelligent Data Processing, Analysis and Control in Complex Systems; Advanced Neural Network Theory and Algorithms; Advanced Computational Methods and Applications; Fuzzy, Neural, and Fuzzy-neuro Hybrids; Intelligent Modelling, Monitoring, and Control of Complex Nonlinear Systems; Intelligent manufacturing, autonomous systems, intelligent robotic systems; Computational Intelligence and Applications.
Energy Storage Devices for Renewable Energy-Based Systems: Rechargeable Batteries and Supercapacitors, Second Edition is a fully revised edition of this comprehensive overview of the concepts, principles and practical knowledge on energy storage devices. The book gives readers the opportunity to expand their knowledge of innovative supercapacitor applications, comparing them to other commonly used energy storage devices. With new application case studies and definitions, this resource will strengthen your understanding of energy storage from a practical, applications-based point-of-view without requiring detailed examination of underlying electrochemical equations. Users will learn about various design approaches and real-time applications of ESDs. Electronic engineering experts and system designers will find this book useful to deepen their understanding on the application of electronic storage devices, circuit topologies, and industrial device data sheets to develop new applications. The book is also intended to be used as a textbook for masters and doctoral students who want to enhance their knowledge and understanding the concepts of renewable energy sources and state-of-the-art ESDs. - Provides explanations of the latest energy storage devices in a practical applications-based context - Includes examples of circuit designs that optimize the use of supercapacitors - Highlights the unique benefits of these devices
This book constitutes the refereed proceedings of the 13th International Conference on Formal Modeling and Analysis of Timed Systems, FORMATS 2015, held in Madrid, Spain, in September 2015. The conference was organized under the umbrella of Madrid Meet 2015, a one week event focussing on the areas of formal and quantitative analysis of systems, performance engineering, computer safety, and industrial critical applications. The 19 papers presented in this volume were carefully reviewed and selected from 42 initial submissions.
