Power Quality In Microgrids Issues Challenges And Mitigation Techniques
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Power Quality in Microgrids: Issues, Challenges and Mitigation Techniques
Author: Surender Reddy Salkuti
language: en
Publisher: Springer Nature
Release Date: 2023-06-13
This book provides a brief insight of various challenges and its mitigation techniques in microgrid due to power quality (PQ) issues. The central concept of this book revolves around the PQ issues in microgrid. The main objective of this book is to make aware of the power and control engineers with different innovative techniques to mitigate the challenges due to PQ issues in microgrid. The topics covered in this book are PQ disturbances in microgrid and different recent and innovative schemes to mitigate them. The book emphasizes technical issues, theoretical background, and practical applications that drive postgraduates, researchers, and practicing engineers with right advanced skills, vision, and knowledge in finding microgrid power quality issues, various technical challenges and providing mitigation techniques for the future sustainable microgrids.
NanoMind: Exploring Synergies in Nanotechnology and Machine Learning
NanoMind" serves as a captivating exploration at the crossroads of nanotechnology and machine learning, revealing the profound synergies between these two groundbreaking fields. At its core, the book is a guided tour through the intricate realms of nanoscale materials and artificial intelligence, illuminating their combined potential to reshape the landscape of innovation. The journey begins with an introductory chapter, setting the stage for the convergence of nanotechnology and machine learning. Readers are introduced to the fundamental principles and applications of nanoscale materials, laying the groundwork for a deeper understanding of the nano-world. Simultaneously, the basics of machine learning are demystified, providing a comprehensive overview of the methodologies and concepts that underpin AI. "Nanoscale Sensing and Imaging" takes readers into the realm of advanced technologies, showcasing how machine learning enhances our ability to sense and image materials at the nanoscale. The narrative then seamlessly transitions to the creation and optimization of materials with nano-enhancements in "Nano-Enabled Materials." This section demonstrates how the marriage of nanotechnology and machine learning can lead to the development of materials with unprecedented properties, fostering innovation in diverse industries. The exploration extends into the field of healthcare with "Machine Learning in Nanomedicine," unveiling how AI at the nanoscale is transforming diagnostics, drug delivery, and personalized medicine. "Quantum Computing and Nanotechnology" delves into the cutting-edge intersection of quantum computing, nanotech, and machine learning, showcasing the potential for revolutionary advancements in computation and problem-solving. However, the journey isn't without its challenges. The book devotes a section to "Challenges and Ethical Considerations," addressing the complexities and ethical dimensions associated with the convergence of nanotechnology and machine learning. This discussion ensures that readers are equipped to navigate the ethical landscape responsibly.
Artificial Intelligence for Integrated Smart Energy Systems in Electric Vehicles
Author: Surender Reddy Salkuti
language: en
Publisher: Springer Nature
Release Date: 2025-07-02
This book provides a comprehensive exploration of cutting-edge research in electric vehicles (EVs) integrated smart energy systems with a main focus on the application of artificial intelligence (AI). This book offers a wide and comprehensive practical approach with the applications of AI to address the challenges and opportunities of modern hybrid energy systems for developing advanced hybrid intelligent methodologies for forecasting and scheduling variable power output from renewable energy sources (RESs) and EVs. This will enhance system flexibility and facilitate the integration of RESs and EVs efficiently, which is a step towards a sustainable future. The chapters cover diverse topics offering valuable knowledge and methodologies including an introduction to Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), Cybersecurity, and their applications in modern power and energy systems, intelligent control of power electronics for RESs and EVs, intelligent charging management of EVs, etc. This book aims to provide insights into various suitable solutions to increase the security, reliability, and interoperability of the grid under high penetration of renewable energy, storage systems, and electric transport in the context of the modern smart grid. The multi-objective optimization problems such as economic and emission dispatch problems; flexibility and reliability problems; and economic and reliability problems are solved to determine the trade-off solutions using efficient evolutionary algorithms. The chapters cover diverse topics offering valuable knowledge and methodologies including an introduction to Artificial Intelligence (AI), Machine Learning (ML), IoT, Cybersecurity, and their applications in modern power and energy systems, intelligent control of power electronics for RESs and EVs, intelligent charging management of EVs, etc.