Advanced Anomaly Detection Technologies And Applications In Energy Systems

This book gives readers the tools to craft AI systems that don't just thrive today, but endure sustainably into the future. Whether a trailblazer or an aspiring innovator, this book enables readers to resonate with the ambitions of software developers, data scientists, and AI practitioners. The author covers the latest techniques and best practices for energy efficiency, reducing carbon footprints, and ensuring fair and ethical AI. The book also addresses important issues such as AI governance, managing risks, and ensuring transparency. Topics covered include understanding the relationship between AI and sustainable development, strategies for building efficient AI systems, and ethical considerations in AI development, among others. The author includes case studies of companies and organizations that have successfully implemented sustainable AI software development practices. Therefore, this book will be of interest to AI practitioners, academics, researchers, and lecturers in computer science, artificial intelligence, machine learning and data sciences.

IoT-Enabled Multi-Energy Systems: From Isolated Energy Grids to Modern Interconnected Networks proposes practical solutions for the management and control of energy interactions throughout the interconnected energy infrastructures of the future multi-energy grid. The book discusses a panorama of modeling, planning and optimization considerations for IoT technologies, their applications across grid modernization, and the coordinated operation of multi-vector energy grids. The work is suitable for energy, power, mechanical, chemical, process and environmental engineers, and highly relevant for researchers and postgraduate students who work on energy systems. Sections address core theoretical underpinnings, significant challenges and opportunities, how to support IoT-based developed expert systems, and how AI can empower IoT technologies to sustainably develop fully renewable modern multi-carrier energy networks. Contributors address artificial intelligence technology and its applications in developing IoT-based technologies, cloud-based intelligent energy management schemes, data science and multi-energy big data analysis, machine learning and deep learning techniques in multi-energy systems, and much more. Reviews core applications of IoT technologies in grid modernization of multi-energy networks Develops practical solutions for optimal integration of renewable energy resources in modern multi-vector energy networks Analyzes the reliable integration, sustainable operation and accurate planning of multi-carrier energy grids in highly penetrated stochastic energy resources