Adaptive Power Quality for Power Management Units using Smart Technologies

Title: Adaptive Power Quality for Power Management Units using Smart Technologies
Author: Arti Vaish, Mokhtar Shouran, Pankaj Kumar Goswami, Surbhi Bhatia
ISBN: 1032392991 / 9781032392998
Format: Hard Cover
Pages: 360
Publisher: CRC Press
Year: 2024
Availability: 2 to 3 weeks.

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This book covers issues associated with smart systems due to the presence of onboard nonlinear components. It discusses the advanced architecture of smart systems for power management units. It explores issues of power management and identifies hazardous signals in the power management units of smart devices. It

  • Presents adaptive artificial intelligence and machine learning-based control strategies.
  • Discusses advanced simulations and data synthesis for various power management issues.
  • Showcases solutions to the uncertainty and reliability issues in power management units.
  • Identifies new power quality challenges in smart devices.
  • Explains hybrid active power filters, shunt hybrid active power filters, and the industrial internet of things in power quality management.

This book comprehensively discusses advancements of traditional electrical grids, the benefits of smart grids to customers and stakeholders, properties of smart grids, smart grid architecture, smart grid communication, and smart grid security. It further covers the architecture of advance power management units (PMU) of smart devices, and the identification of harmonic distortions with respect to various sensor-based technology. It will serve as an ideal reference text for senior undergraduate and graduate students, and academic researchers in fields including electrical engineering, electronics, communications engineering, and computer engineering.

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Preface
Editors
Contributors

Chapter 1 : Machine Learning and 5G-Based Industrial IOT Device Positioning for Location-Aware Power Quality Management
Chapter 2 : Overview and Comparative Application of On-Grid and Off-Grid Renewable Energy Systems in Modern-Day Electrical Power Technology
Chapter 3 : Conceptual Perspective of Renewable Energy Resources : A Paradigm Shift in Combating World Climate Change
Chapter 4 : Quantum Neural Networks for Machine Learning Applied to the Tracking and Control of the Dynamics of Stochastic Transmission Lines
Chapter 5 : Power Grid Adaptive and Block Processing Control Based on the Extended Kalman Filter and Large Deviation Theory
Chapter 6 : Energy-Aware Power Control Scheme for IOT Applications
Chapter 7 : Harmonic Distortions in Smart Devices : A Comprehensive Survey from Conventional to Future Smart IOT Devices
Chapter 8 : Design of Nano- and Microgrids Using the Hetnet Switching Strategy
Chapter 9 : Adaptive Smart Power Saving Techniques for Machine-to-Machine Communication-Enabled Wireless Sensor Networks
Chapter 10 : An Efficient Lightweight Signature Verifiable Scheme for Node Authentication Using Trivariate Polynomials Over Elliptic Curve Cryptography for Decentralized Distributed Public Key Infrastructures
Chapter 11 : Comparative Analysis of Rabbit Message Queue in the Cloud : The Internet of Things
Chapter 12 : Novel Drug Delivery Systems
Chapter 13 : Integration of Blockchain for IOT Communication

Index