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Welcome to IET Digital Library

The IET Digital Library holds more than 190,000 technical papers from 1994 onwards for all IET journals, magazines, books, conference publications and seminar digests. Highly cited journals such as Electronics Letters are available alongside 44 research journal titles, The Journal of Engineering, the IET's gold open access journal, Micro & Nano Letters, the IET's online only journal, the IET's member magazine Engineering & Technology, plus seminar digests and conference publications. Find out more about the Digital Library.

Latest Books

image of Emerging CMOS Capacitive Sensor for Biomedical Applications: A multidisciplinary approach
  • Emerging CMOS Capacitive Sensor for Biomedical Applications: A multidisciplinary approach
  • CMOS-based sensors offer significant advantages to life science applications, such as non-invasive long-term recordings, fast responses and label-free processes. They have been widely applied in many biological and medical fields for the study of living cell samples such as neural cell recording and stimulation, monitoring metabolic activity, cell manipulation, and extracellular pH monitoring. Compared to other sensing techniques, capacitive sensors are low-complexity, high-precision, label-free sensing methods for monitoring cellular activities such as cell viability, proliferation and morphology. The development of capacitive sensors for use in life sciences requires thorough knowledge of both the intended biological applications and CMOS circuitry. This book addresses the principles, design, implementation and testing, and packaging of CMOS circuits for these applications. Existing applications, markets, and potential future developments are also covered, plus the relevant biological protocols. Emerging CMOS Capacitive Sensors for Biomedical Applications provides information and guidance for researchers and advanced students in the field of microelectronics who are looking to specialise in biological applications. It is also relevant to academic and industrial researchers already working in the biosensors field, who wish to expand their knowledge and keep abreast of new developments.

image of Reliability of Power Electronics Converters for Solar Photovoltaic Applications
  • Reliability of Power Electronics Converters for Solar Photovoltaic Applications
  • The importance of power electronic converters for electricity grid equipment is increasing due to the growing distribution-level penetration of renewable energy sources. The performance of the converters mostly depends on interactions between sources, loads, and their state of operation. These devices must be operated with safety and stability under normal conditions, fault conditions, overloads, as well as different operation modes. Therefore, enhanced control strategies of power electronic converters are necessary to improve system stability. This book for researchers and practitioners discusses enhanced control strategies, fault and failure mode classification mechanisms, and reliability analysis methods for PV modules, power electronic converters, and grid-connected PV systems, and thermal image-based monitoring. The technologies conveyed serve to improve the reliability and stability of power systems. Life calculation of converters, and case and reliability studies are included as well. The international author team consists of researchers with a range of backgrounds from academia and industry.

image of Lithium-ion Batteries Enabled by Silicon Anodes
  • Lithium-ion Batteries Enabled by Silicon Anodes
  • Deploying lithium-ion (Li-ion) batteries depends on cost-effective electrode materials with high energy and power density to facilitate lower weight and volume. Si-based anode materials theoretically offer superior lithium storage capacity. Replacing a graphite anode with high-capacity materials such as silicon will further improve the energy density. Durable, low-cost, and high-energy-density materials are vital to developing plug-in electric vehicles as affordable and convenient as gasoline-powered ones, while reducing carbon emissions. This reference presents the knowledge gained over recent decades in the materials science and chemistry of silicon and its derivates as anode materials for Li-ion batteries, and provides insights into developing Si-based anode materials for next-generation batteries. Coverage includes the structure and chemistry of silicon, electrolytes and chemistry of Si anodes, nanostructure and binder additives for Si anodes, surface modification and mechanical properties. Researchers in academia and industry will find this detailed reference a highly useful resource.

image of Model Predictive Control for Microgrids: From power electronic converters to energy management
  • Model Predictive Control for Microgrids: From power electronic converters to energy management
  • Microgrids have emerged as a promising solution for accommodating the integration of renewable energy resources. But the intermittency of renewable generation is posing challenges such as voltage/frequency fluctuations, and grid stability issues in grid-connected modes. Model predictive control (MPC) is a method for controlling a process while satisfying a set of constraints. It has been in use for chemical plants and in oil refineries since the 1980s, but in recent years has been deployed for power systems and electronics as well. This concise work for researchers, engineers and graduate students focuses on the use of MPC for distributed renewable power generation in microgrids. Fluctuating outputs from renewable energy sources and variable load demands are covered, as are control design concepts. The authors provide examples and case studies to validate the theory with both simulation and experimental results and review the shortcomings and future developments. Chapters treat power electronic converters and control; modelling and hierarchical control of microgrids; use of MPC for PV and wind power; voltage support; parallel PV-ESS microgrids; secondary restoration capability; and tertiary power flow optimization.

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image of Space Robotics and Autonomous Systems: Technologies, advances and applications
  • Space Robotics and Autonomous Systems: Technologies, advances and applications
  • Space robotics and autonomous systems (Space RAS) play a critical role in the current and future development of mission-defined machines that can survive in space while performing exploration, assembly, construction, maintenance and servicing tasks. They represent a multi-disciplinary emerging field at the intersection of space engineering, terrestrial robotics, computer science and materials. The field is essential to humankind's ability to explore or operate in space; providing greater access beyond human spaceflight limitations in the harsh environment of space, and offering greater operational handling that extends astronauts' capabilities. Space RAS covers all types of robotics for the exploration of planet surfaces as well as robotics used in orbit around the Earth and the sensors needed by the platform for navigation or control. Written by a team of International experts on space RAS, this book covers advanced research, technologies and applications including: sensing and perception to provide situational awareness for space robotic agents, explorers and assistants; mobility to reach and operate at sites of scientific interest on extra-terrestrial surfaces or free space environments using locomotion; manipulations to make intentional changes in the environment or objects using locomotion such as placing, assembling, digging, trenching, drilling, sampling, grappling and berthing; high-level autonomy for system and sub-systems to provide robust and safe autonomous navigation, rendezvous and docking capabilities and to enable extended-duration operations without human interventions to improve overall performance of human and robotic missions; human-robot interaction and multi-modal interaction; system engineering to provide a framework for understanding and coordinating the complex interactions of robots and achieving the desired system requirements; verification and validation of complex adaptive systems; modelling and simulation; and safety and trust.

image of Utility-scale Wind Turbines and Wind Farms
  • Utility-scale Wind Turbines and Wind Farms
  • Wind power is a pillar of low emission energy systems. Designing more efficient wind turbines and farms, and increasing reliability and flexibility, is an area of intense research and development. In order to overcome the intermittent character of wind power, both the individual turbines and the wind farm as a whole must be considered. Many recent advances have been achieved in multiple aspects of utility-scale wind power. This structured research review conveys recent progress, with chapters written by an international team of experts. Organized into five parts, the book covers the aerodynamics of turbines and farms including layout; control techniques; environmental concerns including noise and bird and bat collisions; the intermittency issue including forecasting, storage and hybrid wind-PV plants; and offshore wind farms. From the general principles of aerodynamics to detailed and systematic coverage of the latest developments, Utility-scale Wind Turbines and Wind Farms provides a convenient and up-to-date source of information for academic researchers and R&D professionals working in this field.

image of Artificial Intelligence for Smarter Power Systems: Fuzzy logic and neural networks
  • Artificial Intelligence for Smarter Power Systems: Fuzzy logic and neural networks
  • The urgent need to reduce carbon emissions is leading to growing use of renewable electricity, particularly from wind and photovoltaics. However, the intermittent nature of these power sources presents challenges to power systems, which need to ensure high and consistent power quality. Going forward, power systems also need to be able to respond to changes in loads, for example from EV charging. Neither production nor load changes can be predicted precisely, and so there is a degree of uncertainty or fuzziness. One way to meet these challenges is to use a kind of artificial intelligence - fuzzy logic. Fuzzy logic uses variables that may be any real number between 0 and 1, rather than either 0 or 1. It has obvious advantages when used for optimization of alternative and renewable energy systems. The parametric fuzzy algorithm is inherently adaptive because the coefficients can be altered to accommodate requirements and data availability. This book focuses on the use of fuzzy logic and neural networks to control power grids and adapt them to changing requirements. Chapters cover fuzzy inference, fuzzy logic-based control, feedback and feedforward neural networks, competitive and associate neural networks, and applications of fuzzy logic, deep learning and big data in power electronics and systems.

image of Handbook of Big Data Analytics. Volume 1: Methodologies
  • Handbook of Big Data Analytics. Volume 1: Methodologies
  • Big Data analytics is the complex process of examining big data to uncover information such as correlations, hidden patterns, trends and user and customer preferences, to allow organizations and businesses to make more informed decisions. These methods and technologies have become ubiquitous in all fields of science, engineering, business and management due to the rise of data-driven models as well as data engineering developments using parallel and distributed computational analytics frameworks, data and algorithm parallelization, and GPGPU programming. However, there remain potential issues that need to be addressed to enable big data processing and analytics in real time. In the first volume of this comprehensive two-volume handbook, the authors present several methodologies to support Big Data analytics including database management, processing frameworks and architectures, data lakes, query optimization strategies, towards real-time data processing, data stream analytics, Fog and Edge computing, and Artificial Intelligence and Big Data. The second volume is dedicated to a wide range of applications in secure data storage, privacy-preserving, Software Defined Networks (SDN), Internet of Things (IoTs), behaviour analytics, traffic predictions, gender based classification on e-commerce data, recommender systems, Big Data regression with Apache Spark, visual sentiment analysis, wavelet Neural Network via GPU, stock market movement predictions, and financial reporting. The two-volume work is aimed at providing a unique platform for researchers, engineers, developers, educators and advanced students in the field of Big Data analytics.

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