Vinay Rishiwal – författare

Introduction to AI techniques for Renewable Energy System

Artificial Intelligence (AI) techniques play an essential role in modeling, analysis, and prediction of the performance and control of renewable energy. The algorithms used to model, control, or predict performances of the energy systems are complicated, involving differential equations, enormous computing power, and time requirements. Instead of complex rules and mathematical routines, AI techniques can learn critical information patterns within a multidimensional information domain. Design, control, and operation of renewable energy systems require a long-term series of meteorological data such as solar radiation, temperature, or wind data. Such long-term measurements are often non-existent for most of the interest locations or, wherever they are available, they suffer from several shortcomings, like inferior quality of data, and in-sufficient long series. The book focuses on AI techniques to overcome these problems. It summarizes commonly used AI methodologies in renewal energy, with a particular emphasis on neural networks, fuzzy logic, and genetic algorithms. It outlines selected AI applications for renewable energy. In particular, it discusses methods using the AI approach for prediction and modeling of solar radiation, seizing, performances, and controls of the solar photovoltaic (PV) systems.

Features

This book, which includes real-life examples, is aimed at undergraduate and graduate students and academicians studying AI techniques used in renewal energy systems.

Introduction to AI techniques for Renewable Energy System

Artificial Intelligence (AI) techniques play an essential role in modeling, analysis, and prediction of the performance and control of renewable energy. The algorithms used to model, control, or predict performances of the energy systems are complicated, involving differential equations, enormous computing power, and time requirements. Instead of complex rules and mathematical routines, AI techniques can learn critical information patterns within a multidimensional information domain. Design, control, and operation of renewable energy systems require a long-term series of meteorological data such as solar radiation, temperature, or wind data. Such long-term measurements are often non-existent for most of the interest locations or, wherever they are available, they suffer from several shortcomings, like inferior quality of data, and in-sufficient long series. The book focuses on AI techniques to overcome these problems. It summarizes commonly used AI methodologies in renewal energy, with a particular emphasis on neural networks, fuzzy logic, and genetic algorithms. It outlines selected AI applications for renewable energy. In particular, it discusses methods using the AI approach for prediction and modeling of solar radiation, seizing, performances, and controls of the solar photovoltaic (PV) systems.

Features

This book, which includes real-life examples, is aimed at undergraduate and graduate students and academicians studying AI techniques used in renewal energy systems.

This book provides a comprehensive overview of blockchain for 6G-enabled network-based applications. Following the key services of blockchain technology, this book will be instrumental to ideate and understand the necessities, challenges, and various case studies of different 6G-based applications. The emphasis is on understanding the contributions of blockchain technology in 6G-enabled applications, and its aim is to give insights into evolution, research directions, challenges, and the ways to empower 6G applications through blockchain.

Blockchain and its applications in 6G-enabled applications can drive many powerful solutions to real-world technical, scientific, and social problems. This book presents the most recent and exciting advances in blockchain for 6G-enabled network applications. Overall, this book is a complete outlet and is designed exclusively for professionals, scientists, technologists, developers, designers, and researchers in network technologies around blockchain integration with IoT, blockchain technology, information technology, and 6G-enabled industrial applications. Secondary readers include professionals involved in policy making and administration, security of public data and law, network policy developers, blockchain technology experts, regulators, and decision makers in government administrations.

This book provides a comprehensive overview of blockchain for 6G-enabled network-based applications. Following the key services of blockchain technology, this book will be instrumental to ideate and understand the necessities, challenges, and various case studies of different 6G-based applications. The emphasis is on understanding the contributions of blockchain technology in 6G-enabled applications, and its aim is to give insights into evolution, research directions, challenges, and the ways to empower 6G applications through blockchain.

Blockchain and its applications in 6G-enabled applications can drive many powerful solutions to real-world technical, scientific, and social problems. This book presents the most recent and exciting advances in blockchain for 6G-enabled network applications. Overall, this book is a complete outlet and is designed exclusively for professionals, scientists, technologists, developers, designers, and researchers in network technologies around blockchain integration with IoT, blockchain technology, information technology, and 6G-enabled industrial applications. Secondary readers include professionals involved in policy making and administration, security of public data and law, network policy developers, blockchain technology experts, regulators, and decision makers in government administrations.

This book discusses integration of internet of things (IoT), cloud computing, and big data. It presents a unique platform where IoT, cloud computing, and big data are fused together and can be foreseen as a perfect solution to many applications. Usually, IoT, cloud computing, and big data are researched separately on the basis of their properties, underlying technologies, and other open issues. Integration of IoT, cloud computing and big data is not that easy and can face key open issues like standardization of interfaces, power and energy efficiency in both data processing and transmission, security and privacy, storage mechanisms for future applications, scalability and flexibility, and QoS provisioning for end user applications. Integration of IoT, cloud computing, and big data represents the next big rise for future industry and business applications. This integration opens new exhilarating directions for research and it is discussed in this book.