Modeling And Control Of Static Converters For Hybrid Storage Systems

The energy transition initiated in recent years has enabled the growing integration of renewable production into the energy mix. Microgrids make it possible to maximize the efficiency of energy transmission from source to consumer by bringing the latter together geographically and by reducing losses linked to transport. However, the lack of inertia and the micro-grid support system makes it weak, and energy storage is necessary to ensure its proper functioning. Current storage technologies do not make it possible to provide both a large capacity of energy and power at the same time. Hybrid storage is a solution that combines the advantages of several technologies and reduces their disadvantages. Modeling and Control of Static Converters for Hybrid Storage Systems covers the modeling, control theorems, and optimization techniques that solve many scientific problems for researchers in the field of power converter control for renewable energy hybrid storage and places particular emphasis on the modeling and control of static converters for hybrid storage systems. Covering topics ranging from energy storage to power generation, this book is ideal for automation engineers, electrical engineers, mechanical engineers, professionals, scientists, academicians, master's and doctoral students, and researchers in the disciplines of electrical and mechanical engineering.

As wireless services rapidly expand, the inefficient use of limited spectrum resources poses a critical challenge. The conventional approach to spectrum allocation, based on fixed assignments, could be more effective in meeting the escalating demand for wireless devices and systems. Cognitive radio technology offers a transformative solution by reimagining the spectrum as a multidimensional space, enabling opportunistic access to underutilized bands. However, the field of cognitive radio is still in its early stages, needing more in-depth analyses and descriptions of crucial processes. Spectrum and Power Allocation in Cognitive Radio Systems addresses this pressing need by offering a comprehensive guide for academic scholars, researchers, and industry professionals. This book delves into cognitive radio technology's foundations, organization, and challenges, providing insights into dynamic spectrum access, networking protocols, hardware architecture, and emerging applications. It presents advanced topics such as spectrum sensing algorithms, cooperative spectrum sensing, and multi-user access, offering practical solutions to enhance spectrum efficiency.

In the age of immediate technical expansion, our world faces a multifaceted challenge: ensuring the sustainability of our digital transformation. Governments and organizations have wholeheartedly embraced innovative technologies such as artificial intelligence, blockchain, and e-governance, but in doing so, they have encountered a complex web of issues. These range from cybersecurity concerns in an increasingly digitalized world to the need for intelligent systems capable of managing automation infrastructure and interconnected environments. Sustainable Development in AI, Blockchain, and E-Governance Applications offers a forward-thinking approach that harnesses the synergy between intelligent systems, machine learning, deep learning, and blockchain methods. It explores data-driven decision-making, automation infrastructure, autonomous transportation, and the creation of connected buildings, all aimed at crafting a sustainable digital future. By delving into topics like machine learning for smart parking, disease classification through neural networks, and the Internet of Things (IoT) for smarter cities, this book equips academic scholars with the tools they need to navigate the complex terrain of technology and governance. Academic scholars and researchers in technology, governance, and sustainability will find this book to be an indispensable resource. It caters to those seeking a comprehensive understanding of current and future trends in the integration of intelligent systems with cybersecurity applications.

The world is confronting the reality of climate change, which transcends geographical boundaries, necessitating a multidisciplinary approach. Effective mitigation strategies for climate change demand diversity, inclusion, equity, and collaboration as paramount considerations in the formulation and execution of mitigation strategies. Global Perspectives on Climate Change, Social Resilience, and Social Inclusion illuminates the interplay between climate shifts and society's complex tapestry. Authored by leading sociologists and interdisciplinary scholars, this researched volume offers an exploration of climate change through the lens of sociology, unveiling its implications for our global community. Moreover, the book spotlights the proactive voices of voluntary associations and activists dedicated to championing climate change victims' rights. Their collective message resonates throughout: mitigating climate change risks must be integrated into a broader framework of resilient development, elevating the economic standing and quality of life for disadvantaged groups while fostering equity across all strata of society. This book is ideal for scholars, policymakers, and activists seeking a nuanced understanding of the intricate interplay between climate change and the social fabric of our world.

In the ever-evolving landscape of engineering, a pressing challenge looms large—the need to navigate the complexities of modern problems with precision and efficiency. As industries grapple with an array of intricate issues, from sustainable materials to resilient infrastructure, the demand for optimal solutions has never been more pronounced. Traditional approaches are often inadequate, prompting the search for advanced optimization techniques capable of unraveling the intricacies inherent in engineering systems. The problem at hand is clear: how can engineers, researchers, and practitioners harness cutting-edge methodologies to address the multifaceted challenges shaping our technological future? Advanced Optimization Applications in Engineering, is a definitive guide poised to revolutionize problem-solving in civil engineering. This book offers a comprehensive exploration of state-of-the-art optimization algorithms and their transformative applications. By delving into genetic algorithms, particle swarm optimization, neural networks, and other metaheuristic strategies, this collection provides a roadmap for automating design processes, reducing costs, and unlocking innovative solutions. The chapters not only introduce these advanced techniques but also showcase their practical implementation across diverse engineering domains, making this book an indispensable resource for those seeking to stay at the forefront of technological advancements.

In the present era, technological developments are increasing the efficiency and potential of each stakeholder in a business. Robotic process automation is one of the key areas that can be applied in business organizations and corporate sectors to enhance productivity and show a path to success. Application and Adoption of Robotic Process Automation for Smart Cities provides relevant theoretical frameworks and various developments in the area of robotic process automation. Covering topics such as banking and financial services, public engagement, and smart cities, this premier reference source is a valuable resource for business leaders, IT managers, government officials, engineers, students and educators of higher education, researchers, and academicians.

In today's digital age, the rapid advancement of AI and digital technologies has led to the emergence of digital consciousness, blurring the lines between human and machine thinking. At the same time, these technologies offer unprecedented convenience and efficiency but pose significant challenges. Individuals are increasingly facing issues such as stress, anxiety, and technology addiction, impacting their overall well-being and decision-making processes. The dichotomy between digital consciousness and human consciousness raises critical questions about how we can navigate these challenges in a rapidly evolving technological landscape. To address these pressing concerns, Comparative Analysis of Digital Consciousness and Human Consciousness: Bridging the Divide in AI Discourse offers a comprehensive exploration of the impacts of digital consciousness on human well-being and decision-making. This book delves into the paradoxes and challenges posed by the coexistence of digital and human consciousness, providing insights from psychological perspectives, practitioner experiences, and academic research. By offering a nuanced understanding of these concepts, we aim to equip readers with the knowledge and tools needed to manage the implications of digital consciousness in their personal and professional lives.

Quantum computing is radically different from the conventional approach of transforming bit-strings from one set of zeros and ones to another. With quantum computing, everything changes. The physics used to understand bits of information and the devices that manipulate them are vastly different. Quantum engineering is a revolutionary approach to quantum technology. Technology Road Mapping for Quantum Computing and Engineering explores all the aspects of quantum computing concepts, engineering, technologies, operations, and applications from the basics to future advancements. Covering topics such as machine learning, quantum software technology, and technology road mapping, this book is an excellent resource for data scientists, engineers, students and professors of higher education, computer scientists, researchers, and academicians.

In the swiftly evolving realm of technology, the challenge of classical computing's constraints in handling intricate problems has become pronounced. While classical computers excel in many areas, they struggle with complex issues in cryptography, optimization, and molecular simulation. Addressing these escalating challenges requires a disruptive solution to push the boundaries of computation and innovation. Principles and Applications of Quantum Computing Using Essential Math, authored by A. Daniel, M. Arvindhan, Kiranmai Bellam, and N. Krishnaraj. This guide pioneers the transformative potential of quantum computing by seamlessly blending rigorous mathematics with quantum theory. It equips scholars, researchers, and aspiring technologists with insights to grasp and harness quantum computing's capabilities. By delving into quantum gates, algorithms, and error correction techniques, the book demystifies quantum computing, inviting exploration of quantum machine learning, cryptography, and the dynamic interplay between classical and quantum computing. As the quantum landscape expands, this book acts as a vital companion, navigating readers through the converging realms of industry, academia, and innovation. Principles and Applications of Quantum Computing Using Essential Math arrives as a timely answer to the limitations of classical computing, providing scholars with an essential roadmap to navigate the quantum technology landscape. With its clear explanations, practical applications, and forward-looking perspectives, this book serves as an indispensable tool for unraveling quantum computing's mysteries and driving innovation into uncharted domains.

In our data-rich era, extracting meaningful insights from the vast amount of information has become a crucial challenge, especially in government service delivery where informed decisions are paramount. Traditional approaches struggle with the enormity of data, highlighting the need for a new approach that integrates data science and machine learning. The book, Machine Learning and Data Science Techniques for Effective Government Service Delivery, becomes a vital resource in this transformation, offering a deep understanding of these technologies and their applications. Within the complex landscape of modern governance, this book stands as a solution-oriented guide. Recognizing data's value in the 21st century, it navigates the world of data science and machine learning, enhancing the mechanics of government service. By addressing citizens' evolving needs, these advanced methods counter inefficiencies in traditional systems. Tailored for experts across technology, academia, and government, the book bridges theory and practicality. Covering foundational concepts and innovative applications, it explores the potential of data-driven decision-making for a more efficient and citizen-centric government future.