Adaptive Power Quality For Power Management Units Using Smart Technologies
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Adaptive Power Quality for Power Management Units using Smart Technologies
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.
Adaptive Power Quality for Power Management Units using Smart Technologies
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.
Industry 6.0
What are the means to create a paradigm shift from conventional to intelligent companies? Industry 6.0: Technology, Practices, Challenges and Applications shows how integrating Industry 6.0 technology with data creates a framework for that shift. The book discusses the limitations, pitfalls, and open research questions in Industry 6.0, as well as the most recent advances, architectures, frameworks, applications, and novel practices, methods, and techniques. These are vital for resolving intelligent Internet of Things issues. There is a special focus on sustainable growth, humanization and environmentally friendly intelligent system applications, and an emphasis on the latest innovations in intelligent systems in classical machine learning, deep learning, Internet of Things (IoT), Industrial Internet of Things (IIoT), blockchain, knowledge representation, knowledge management, big data, and natural language processing (NLP). Features: Presents the latest trends in the fields of intelligent systems, machine intelligence, deep learning, and Industrial Internet of Things for smart environments. Discusses securing the mobile ad hoc network (MANET) by detecting the Intrusions using CSO and XGBoost model. Highlights the methods of smart things in collaborative autonomous fleets and platforms for integrating applications across different business and industry domains. Focuses on intelligent process manufacturing, automation using robotics, development of robotic appliances, and smart manufacturing. Covers data-driven agriculture, crop disease prediction, drip irrigation systems, pesticide and fertilizer sprinkling using the Industrial Internet of Things, and water estimation systems. With many contemporary articles from both scientists and practitioners working in many fields where intelligent systems and the IIoT can break new ground, the text is assembled to aim at a readership that includes researchers, statisticians, practitioners, scientists, and developers.