Anand Kumar Gupta – författare

Artificial Intelligence for Sustainable Energy Systems 1 presents a comprehensive exploration of how intelligent technologies are transforming modern energy infrastructures toward a more sustainable and efficient future. This book brings together the fundamental concepts of artificial intelligence (AI), machine learning, deep learning and big data analytics, with their practical integration into renewable energy systems, smart grids and digital energy management platforms. The book covers key developments such as AI-driven renewable optimization, predictive modeling for energy demand, digital twins for asset maintenance, blockchain-enabled energy trading, IoT-based smart grids and intelligent monitoring systems. By blending theoretical insights with real-world technological implementations, the book highlights how data-driven intelligence enhances reliability, security and sustainability across energy ecosystems. Designed for researchers, engineers, graduate students and policymakers, this book serves as a fundamental reference for advancing intelligent solutions in next-generation sustainable energy systems.

Artificial Intelligence for Sustainable Energy Systems 1 presents a comprehensive exploration of how intelligent technologies are transforming modern energy infrastructures toward a more sustainable and efficient future. This book brings together the fundamental concepts of artificial intelligence (AI), machine learning, deep learning and big data analytics, with their practical integration into renewable energy systems, smart grids and digital energy management platforms. The book covers key developments such as AI-driven renewable optimization, predictive modeling for energy demand, digital twins for asset maintenance, blockchain-enabled energy trading, IoT-based smart grids and intelligent monitoring systems. By blending theoretical insights with real-world technological implementations, the book highlights how data-driven intelligence enhances reliability, security and sustainability across energy ecosystems. Designed for researchers, engineers, graduate students and policymakers, this book serves as a fundamental reference for advancing intelligent solutions in next-generation sustainable energy systems.

Artificial Intelligence for Sustainable Energy Systems 2 presents a comprehensive exploration of how intelligent technologies are transforming modern energy infrastructures toward a more sustainable and efficient future. This book brings together the fundamental concepts of artificial intelligence (AI), machine learning, deep learning and big data analytics, with their practical integration into renewable energy systems, smart grids and digital energy management platforms. The book covers key developments such as AI-driven renewable optimization, predictive modeling for energy demand, digital twins for asset maintenance, blockchain-enabled energy trading, IoT-based smart grids and intelligent monitoring systems. By blending theoretical insights with real-world technological implementations, the book highlights how data-driven intelligence enhances reliability, security and sustainability across energy ecosystems. Designed for researchers, engineers, graduate students and policymakers, this book serves as a fundamental reference for advancing intelligent solutions in next-generation sustainable energy systems.

Artificial Intelligence for Sustainable Energy Systems 2 presents a comprehensive exploration of how intelligent technologies are transforming modern energy infrastructures toward a more sustainable and efficient future. This book brings together the fundamental concepts of artificial intelligence (AI), machine learning, deep learning and big data analytics, with their practical integration into renewable energy systems, smart grids and digital energy management platforms. The book covers key developments such as AI-driven renewable optimization, predictive modeling for energy demand, digital twins for asset maintenance, blockchain-enabled energy trading, IoT-based smart grids and intelligent monitoring systems. By blending theoretical insights with real-world technological implementations, the book highlights how data-driven intelligence enhances reliability, security and sustainability across energy ecosystems. Designed for researchers, engineers, graduate students and policymakers, this book serves as a fundamental reference for advancing intelligent solutions in next-generation sustainable energy systems.

Artificial Intelligence for Sustainable Energy Systems 1 presents a comprehensive exploration of how intelligent technologies are transforming modern energy infrastructures toward a more sustainable and efficient future. This book brings together the fundamental concepts of artificial intelligence (AI), machine learning, deep learning and big data analytics, with their practical integration into renewable energy systems, smart grids and digital energy management platforms. The book covers key developments such as AI-driven renewable optimization, predictive modeling for energy demand, digital twins for asset maintenance, blockchain-enabled energy trading, IoT-based smart grids and intelligent monitoring systems. By blending theoretical insights with real-world technological implementations, the book highlights how data-driven intelligence enhances reliability, security and sustainability across energy ecosystems. Designed for researchers, engineers, graduate students and policymakers, this book serves as a fundamental reference for advancing intelligent solutions in next-generation sustainable energy systems.

Artificial Intelligence for Sustainable Energy Systems 2 presents a comprehensive exploration of how intelligent technologies are transforming modern energy infrastructures toward a more sustainable and efficient future.This book brings together the fundamental concepts of artificial intelligence (AI), machine learning, deep learning and big data analytics, with their practical integration into renewable energy systems, smart grids and digital energy management platforms. The book covers key developments such as AI-driven renewable optimization, predictive modeling for energy demand, digital twins for asset maintenance, blockchain-enabled energy trading, IoT-based smart grids and intelligent monitoring systems. By blending theoretical insights with real-world technological implementations, the book highlights how data-driven intelligence enhances reliability, security and sustainability across energy ecosystems.Designed for researchers, engineers, graduate students and policymakers, this book serves as a fundamental reference for advancing intelligent solutions in next-generation sustainable energy systems.