The book aims to equalize the theoretical involvement with industrial practicality and build a bridge between academia and industry by reducing the mathematical difficulties. It provides an overview of distributed control and distributed optimization theory, followed by specific details on industrial applications to smart grid systems, with a special focus on micro grid systems. Each of the chapters is written and organized with an introductory section tailored to provide the essential background of the theories required. The text includes industrial applications to realistic renewable energy systems problems and illustrates the application of proposed toolsets to control and optimization of smart grid systems.

Smart Power Distribution Systems: Control, Communication, and Optimization explains how diverse technologies work to build and maintain smart grids around the globe. Yang, Yang and Li present the most recent advances in the control, communication and optimization of smart grids and provide unique insight into power system control, sensing and communication, and optimization technologies. The book covers control challenges for renewable energy and smart grids, communication in smart power systems, and optimization challenges in smart power system operations. Each area discussed focuses on the scientific innovations relating to the approaches, methods and algorithmic solutions presented. Readers will develop sound knowledge and gain insights into the integration of renewable energy generation in smart power distribution systems. - Presents the latest technological advances in electric power distribution networks, with a particular focus on methodologies, approaches and algorithms - Provides insights into the most recent research and developments from expert contributors from across the world - Presents a clear and methodical structure that guides the reader through discussion and analysis, providing unique insights and sound knowledge along the way

Smart grid (SG), also called intelligent grid, is a modern improvement of the traditional power grid that will revolutionize the way electricity is produced, delivered, and consumed. Studying key concepts such as advanced metering infrastructure, distribution management systems, and energy management systems will support the design of a cost-effective, reliable, and efficient supply system, and will create a real-time bidirectional communication means and information exchange between the consumer and the grid operator of electric power. Optimizing and Measuring Smart Grid Operation and Control is a critical reference source that presents recent research on the operation, control, and optimization of smart grids. Covering topics that include phase measurement units, smart metering, and synchrophasor technologies, this book examines all aspects of modern smart grid measurement and control. It is designed for engineers, researchers, academicians, and students.

Distributed Control and Cyber Security Issues in Microgrids presents a thorough treatment of distributed control methods and cyber security issues for power system researchers and engineers. With the help of mathematical tools, this reference gives a deep understanding of microgrids and new research directions, addressing emerging concepts, methodologies and applications of monitoring, control and protection in smart microgrids with large-scale renewables. With the integration of more distributed or aggregated renewables and the wide utilization of power electronic devices, the smart microgrid is facing new stability and security challenges. - Includes global case studies to demonstrate distributed control success stories - Offers detailed illustrations and flowcharts to address challenges and technical solutions for those working in power systems in utilities and industry - Showcases new challenges faced in the stability and security of smart microgrids

Operation of Distributed Energy Resources in Smart Distribution Networks defines the barriers and challenges of smart distribution networks, ultimately proposing optimal solutions for addressing them. The book considers their use as an important part of future electrical power systems and their ability to improve the local flexibility and reliability of electrical systems. It carefully defines the concept as a radial network with a cluster of distributed energy generations, various types of loads, and energy storage systems. In addition, the book details how the huge penetration of distributed energy resources and the intermittent nature of renewable generations may cause system problems. Readers will find this to be an important resource that analyzes and introduces the features and problems of smart distribution networks from different aspects. - Integrates different types of elements, including electrical vehicles, demand response programs, and various renewable energy sources in distribution networks - Proposes optimal operational models for the short-term performance and scheduling of a distribution network - Discusses the uncertainties of renewable resources and intermittent load in the decision-making process for distribution networks

Distributed generation is becoming more important in electrical power systems due to the decentralization of energy production. Within this new paradigm, new approaches for the operation and planning of distributed power generation are yet to be explored. This book deals with distributed energy resources, such as renewable-based distributed generators and energy storage units, among others, considering their operation, scheduling, and planning. Moreover, other interesting aspects such as demand response, electric vehicles, aggregators, and microgrid are also analyzed. All these aspects constitute a new paradigm that is explored in this Special Issue.

​​Series-Parallel Converter-Based Microgrids: System-Level Control and Stability is the first book to provide a comprehensive and in-depth introduction to the rapid development of series-parallel converter applications in the microgrid system. It provides an advanced and in-depth introduction into all major system modeling, coordinated control, and stability analysis issues, and provides useful methodologies and philosophies for developing new topologies and controls for self-organized decentralized operation of microgrid systems. For each topic, a theoretical introduction and overview are backed by very concrete programming examples that enable the reader to not only understand the topic but to develop microgrid simulation models.

This book gathers contributions from a multidisciplinary research team comprised of control engineering and economics researchers and formed to address a central interdisciplinary social issue, namely economically enabled energy management. The book’s primary focus is on achieving optimal energy management that is viable from both an engineering and economic standpoint. In addition to the theoretical results and techniques presented, several chapters highlight experimental case studies, which will benefit academic researchers and practitioners alike. The first three chapters present comprehensive overviews of respective social contexts, underscore the pressing need for economically efficient energy management systems and academic work on this emerging research topic, and identify fundamental differences between approaches in control engineering and economics. In turn, the next three chapters (Chapters 4–6) provide economics-oriented approaches to the subject. The following five chapters (Chapters 7–11) address optimal energy market design, integrating both physical and economic models. The book’s last three chapters (Chapters 12–14) mainly focus on the engineering aspects of next-generation energy management, though economic factors are also shown to play important roles.

This book presents two nonlinear control strategies for complex dynamical networks. First, sliding-mode control is used, and then the inverse optimal control approach is employed. For both cases, model-based is considered in Chapter 3 and Chapter 5; then, Chapter 4 and Chapter 6 are based on determining a model for the unknow system using a recurrent neural network, using on-line extended Kalman filtering for learning. The book is organized in four sections. The first one covers mathematical preliminaries, with a brief review for complex networks, and the pinning methodology. Additionally, sliding-mode control and inverse optimal control are introduced. Neural network structures are also discussed along with a description of the high-order ones. The second section presents the analysis and simulation results for sliding-mode control for identical as well as non-identical nodes. The third section describes analysis and simulation results for inverse optimal control considering identical or non-identical nodes. Finally, the last section presents applications of these schemes, using gene regulatory networks and microgrids as examples.