Application Of Intelligent Control Algorithms To Study The Dynamics Of Hybrid Power System

This book aims to systematically review and design different intelligent control algorithms for the small-signal stability assessment of HPS. With the growing consciousness of global warming and the fast depletion of natural power generation resources, the existing power system is on the verge of transitions to a “hybrid power system (HPS)” integrated with distributed energy resources. The recent results and requirements for the developments of intelligent control algorithms have motivated the authors to introduce this book for extensively analyzing the performance of HPS against unknown/uncertain disturbances. This book introduces fractional-order resilient control methodologies for arresting small-signal instability of HPS. The prospective investigation has been performed on the MATLAB platform. This book is helpful for undergraduate, postgraduate students, and research scholars working in power system stability, control applications, and soft computing in particular.

The book’s text focuses on explaining and analyzing the dynamic performance of linear and nonlinear systems, in particular for Power Systems (PS) including Hybrid Power Sources (HPS). The system stability is important for both PS operation and planning. Placing emphasis on understanding the underlying stability principles, the book opens with an exploration of basic concepts using mathematical models and case studies from linear and nonlinear system, and continues with complex models and algorithms from field of PS. The book’s features include: (1) progressive approach from simplicity to complexity, (2) deeper look into advanced aspects of stability theory, (3) detailed description of system stability using state space energy conservation principle, (4) review of some research in the field of PS stability analysis, (5) advanced models and algorithms for Transmission Network Expansion Planning (TNEP), (6) Stability enhancement including the use of Power System Stabilizer (PSS) and Flexible Alternative Current Transmission Systems (FACTS), and (7) examination of the influence of nonlinear control on fuel cell HPS dynamics. The book will be easy to read and understand and will be an essential resource for both undergraduate and graduate students in electrical engineering as well as to the PhDs and engineers from this field. It is also a clear and comprehensive reference text for undergraduate students, postgraduate and research students studying power systems, and also for practicing engineers and researchers who are working in electricity companies or in the development of power system technologies. All will appreciate the authors' accessible approach in introduction the power system dynamics and stability from both a mathematical and engineering viewpoint.

The book presents a collection of the high-quality research articles in the field of power engineering, grid integration, energy management, soft computing, artificial intelligence, signal and image processing, data science techniques, and their real-world applications. The papers are presented at International Conference on Power Engineering and Intelligent Systems (PEIS 2023), held during June 24–25, 2023, at National Institute of Technology Delhi, India.

Advanced Frequency Regulation Strategies in Renewable-Dominated Modern Power Systems discusses advanced control strategies positioned to attain stable and reliable electric power operation in highly renewable modern grids. These strategies are increasingly valuable components of the practitioner technical toolbox, and are essential to maintain frequency and voltage regulations, assert power quality standards, and ensure overall grid stability. This book focuses on the rapid integration of renewable-based generating units in power systems, highlighting state-of-the-art technologies and emerging topics pertaining to load frequency control, robust control strategies, and energy storage systems. Chapters are accompanied by case studies drawn from modern international practice. Disseminates novel control strategies for the reliable and robust control of renewable generating units Discusses implementation using case studies that address multiple frequency control applications across integrated modern power systems Accompanied by simulation models in MATLAB that are built to emphasize practical usage and address real-world problems

The editors of this Special Issue titled “Intelligent Control in Energy Systems” have attempted to create a book containing original technical articles addressing various elements of intelligent control in energy systems. In response to our call for papers, we received 60 submissions. Of those submissions, 27 were published and 33 were rejected. In this book, we offer the 27 accepted technical articles as well as one editorial. Authors from 15 countries (China, Netherlands, Spain, Tunisia, United Sates of America, Korea, Brazil, Egypt, Denmark, Indonesia, Oman, Canada, Algeria, Mexico, and the Czech Republic) elaborate on several aspects of intelligent control in energy systems. The book covers a broad range of topics including fuzzy PID in automotive fuel cell and MPPT tracking, neural networks for fuel cell control and dynamic optimization of energy management, adaptive control on power systems, hierarchical Petri Nets in microgrid management, model predictive control for electric vehicle battery and frequency regulation in HVAC systems, deep learning for power consumption forecasting, decision trees for wind systems, risk analysis for demand side management, finite state automata for HVAC control, robust μ-synthesis for microgrids, and neuro-fuzzy systems in energy storage.

This volume aims to provide a state-of-the-art and the latest advancements in the field of intelligent control and smart energy management. Techniques, combined with technological advances, have enabled the deployment of new operating systems in many engineering applications, especially in the domain of transport and renewable resources. The control and energy management of transportation and renewable resources are shifting towards autonomous reasoning, learning, planning and operating. As a result, these techniques, also referred to as autonomous control and energy management, will become practically ubiquitous soon. The discussions include methods, based on neural control (and others) as well as distributed and intelligent optimization. While the theoretical concepts are detailed and explained, the techniques presented are tailored to transport and renewable resources applications, such as smart grids and automated vehicles. The reader will grasp the most important theoretical concepts as well as to fathom the challenges and needs related to timely practical applications. Additional content includes research perspectives and future direction as well as insight into the devising of techniques that will meet tomorrow’s scientific needs. This contributed volume is for researchers, graduate students, engineers and practitioners in the domains of control, energy, and transportation.

INTELLIGENT RENEWABLE ENERGY SYSTEMS This collection of papers on artificial intelligence and other methods for improving renewable energy systems, written by industry experts, is a reflection of the state of the art, a must-have for engineers, maintenance personnel, students, and anyone else wanting to stay abreast with current energy systems concepts and technology. Renewable energy is one of the most important subjects being studied, researched, and advanced in today’s world. From a macro level, like the stabilization of the entire world’s economy, to the micro level, like how you are going to heat or cool your home tonight, energy, specifically renewable energy, is on the forefront of the discussion. This book illustrates modelling, simulation, design and control of renewable energy systems employed with recent artificial intelligence (AI) and optimization techniques for performance enhancement. Current renewable energy sources have less power conversion efficiency because of its intermittent and fluctuating behavior. Therefore, in this regard, the recent AI and optimization techniques are able to deal with data ambiguity, noise, imprecision, and nonlinear behavior of renewable energy sources more efficiently compared to classical soft computing techniques. This book provides an extensive analysis of recent state of the art AI and optimization techniques applied to green energy systems. Subsequently, researchers, industry persons, undergraduate and graduate students involved in green energy will greatly benefit from this comprehensive volume, a must-have for any library. Audience Engineers, scientists, managers, researchers, students, and other professionals working in the field of renewable energy.