Bøger i Studies in Infrastructure and Control serien

This book presents novel idea and concepts developed by the researchers/academia and practicing engineers working in the domain of the power sector infrastructures where power electronics infrastructures are used for improving the system reliability and efficiency in on-grid and off-grid systems. The infrastructures of distributed power generation based on wind, solar, hydro and many other renewable energy sources have increased manifold since last decade due to availability of efficient power converters and small rating generators. The application of power electronics switching devices has made job much easier to make such system infrastructures more reliable and controllable. The power quality (PQ) issues in infrastructures of distributed power generation system are a major concern for customers. The custom power devices such as voltage source converter are used to mitigate the PQ and other issues such as voltage and frequency control under different loading conditions on the supply system. The operation of these custom power devices or other power converters is dependent on the duty cycles generated by control algorithm. The scope of control algorithm may be varying from model predictive control techniques, machine learning techniques to other artificial intelligence-based techniques. In addition to it, some classical control algorithm and adaptive-type control algorithm may also be used for power converter operation. This book creates awareness among teachers, research students and industry persons about better utilization of infrastructures of distributed power generation system by making it more efficient with the use of power electronics and its control.

This book presents the study to design, develop, and implement improved PI control techniques using dead-time compensation, structure enhancements, learning functions and fractional ordering parameters. Two fractional-order PI controllers are proposed and designed: fractional-order predictive PI and hybrid iterative learning based fractional-order predictive PI controller. Furthermore, the proposed fractional-order control strategies and filters are simulated over first- and second-order benchmark process models and further validated using the real-time experimentation of the pilot pressure process plant. In this book, five chapters are structured with a proper sequential flow of details to provide a better understanding for the readers. A general introduction to the controllers, filters and optimization techniques is presented in Chapter 1. Reviews of the PI controllers family and their modifications are shown in the initial part of Chapter 2, followed by the development of the proposed fractional-order predictive PI (FOPPI) controller with dead-time compensation ability. In the first part of chapter 3, a review of the PI based iterative learning controllers, modified structures of the ILC and their modifications are presented. Then, the design of the proposed hybrid iterative learning controller-based fractional-order predictive PI  controller based on the current cyclic feedback structure is presented. Lastly, the results and discussion of the proposed controller on benchmark process models and the real-time experimentation of the pilot pressure process plant are given. Chapter 4 presents the development of the proposed filtering techniques and their performance comparison with the conventional methods. Chapter 5 proposes the improvement of the existing sine cosine algorithm (SCA) and arithmetic optimization algorithm (AOA) to form a novel arithmetic-trigonometric optimization algorithm (ATOA) to accelerate the rate of convergence in lesser iterations with mitigation towards getting caught in the same local position. The performance analysis of the optimization algorithm will be carried out on benchmark test functions and the real-time pressure process plant.

The book investigates the fractional calculus-based approaches and their benefits to adopting in complex real-time areas. Another objective is to provide initial solutions for new areas where fractional theory has yet to verify the expertise. The book focuses on the latest scientific interest and illustrates the basic idea of general fractional calculus with MATLAB codes. This book is ideal for researchers working on fractional calculus theory both in simulation and hardware. Researchers from academia and industry working or starting research in applied fractional calculus methods will find the book most useful. The scope of this book covers most of the theoretical and practical studies on linear and nonlinear systems using fractional-order integro-differential operators.

This book provides an overview of a power transformer infrastructure and comprehensive digital protection of it. It presents various protective methodologies available to protect the transformer from disturbances by taking care of mal-operation due to external disturbances and providing fine protection to the transformer. Though there are many protection methodologies available in the practice. However, these existing methodologies may mal-operate during external disturbances such as inrush, over-fluxing and short circuits. Hence, further research is needed in addition to the existing methods of protection in terms of more fault prediction accuracy, speedy operation, and lower protection cost with zero error in the detection of faults. The book will be useful reference for practitioners from academia and industrial applications.

This book covers complete spectrum of the ICT infrastructure elements required to design, develop and deploy the ICT applications at large scale. Considering the focus of governments worldwide to develop smart cities with zero environmental footprint, the book is timely and enlightens the way forward to achieve the goal by addressing the technological aspects. In particular, the book provides an in depth discussion of the sensing infrastructure, communication protocols, computation frameworks, storage architectures, software frameworks, and data analytics. The book also presents the ICT application-related case studies in the domain of transportation, health care, energy, and disaster management, to name a few. The book is used as a reference for design, development, and large-scale deployment of ICT applications by practitioners, professionals, government officials, and engineering students.

This book provides an overview of how efficient building energy management can be done, considering the increasing importance of renewable energy integration. It also includes the grid-interactive building, their control, energy management, and optimization techniques to promote better understanding among researchers and business professionals in the utility sector and across industries. This book is written and edited by leading specialists active in concurrent developments in smart building management, renewable energy research, and application-driven R&D. The experiences and research work shared help the readers in enhancing their knowledge in the field of renewable energy, power engineering, building energy management, demand, and supply management and learn the technical analysis of the same in an insightful manner. Additionally, established and emerging applications related to applied areas like smart cities, the Internet of things, machine learning, artificial intelligence, etc., are developed and utilized to demonstrate recent innovations in smart building energy management.

This book presents the latest research on applications of artificial intelligence and the Internet of Things in renewable energy systems. Advanced renewable energy systems must necessarily involve the latest technology like artificial intelligence and Internet of Things to develop low cost, smart and efficient solutions. Intelligence allows the system to optimize the power, thereby making it a power efficient system; whereas, Internet of Things makes the system independent of wire and flexibility in operation. As a result, intelligent and IOT paradigms are finding increasing applications in the study of renewable energy systems. This book presents advanced applications of artificial intelligence and the internet of things in renewable energy systems development. It covers such topics as solar energy systems, electric vehicles etc. In all these areas applications of artificial intelligence methods such as artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above, called hybrid systems, are included. The book is intended for a wide audience ranging from the undergraduate level up to the research academic and industrial communities engaged in the study and performance prediction of renewable energy systems.

This book gathers selected high-quality research papers presented at International Conference on Renewable Technologies in Engineering (ICRTE 2021) organized by Manav Rachna International Institute of Research & Studies, Faridabad, Haryana, India, during 15-16 April 2021. The book includes conference papers on the theme "e;Computational Techniques for Renewable Energy Optimization"e;, which aims to bring together leading academic scientists, researchers and research scholars to exchange and share their experiences and research results on all aspects of renewable energy integration, planning, control and optimization. It also provides a premier interdisciplinary platform for researchers, practitioners and educators to present and discuss the most recent innovations, trends and concerns as well as practical challenges encountered and solutions adopted in the fields of renewable energy and resources.

This book mainly focuses on the innovations in intelligent transportation infrastructure and management. The content of the book is selected in such a way that it will cover a wide range of areas to integrate advanced technologies and provide best and innovative solution to problems faced by the rapidly growing transportation sector.

This book presents the latest research on applications of artificial intelligence and the Internet of Things in renewable energy systems. Advanced renewable energy systems must necessarily involve the latest technology like artificial intelligence and Internet of Things to develop low cost, smart and efficient solutions.