In the era of propelling traditional energy systems to evolve towards smart energy systems, including power generation, energy storage systems, and electricity consumption have become more dynamic. The quality and reliability of power supply are impacted by the sporadic and rising use of electric vehicles, and domestic & industrial loads. Similarly, with the integration of solid state devices, renewable sources, and distributed generation, power generation processes are evolving in a variety of ways. Several cutting-edge technologies are necessary for the safe and secure operation of power systems in such a dynamic setting, including load distribution automation, energy regulation and control, and energy trading. This book covers the applications of various big data analytics, artificial intelligence, and machine learning technologies in smart grids for demand prediction, decision-making processes, policy, and energy management. The book delves into the new technologies such as the Internet of Things, blockchain, etc. for smart home solutions, and smart city solutions in depth in the context of the modern power systems. Technical topics discussed in the book include: • Hybrid smart energy system technologies • Energy demand forecasting • Use of different protocols and communication in smart energy systems • Power quality and allied issues and mitigation using AI • Intelligent transportation • Virtual power plants • AI business models.

This book presents innovative research works to automate, innovate, design, and deploy AI fo real-world applications. It discusses AI applications in major cutting-edge technologies and details about deployment solutions for different applications for sustainable development. The application of Blockchain techniques illustrates the ways of optimisation algorithms in this book. The challenges associated with AI deployment are also discussed in detail, and edge computing with machine learning solutions is explained. This book provides multi-domain applications of AI to the readers to help find innovative methods towards the business, sustainability, and customer outreach paradigms in the AI domain. • Focuses on virtual machine placement and migration techniques for cloud data centres • Presents the role of machine learning and meta-heuristic approaches for optimisation in cloud computing services • Includes application of placement techniques for quality of service, performance, and reliability improvement • Explores data centre resource management, load balancing and orchestration using machine learning techniques • Analyses dynamic and scalable resource scheduling with a focus on resource management The reference work is for postgraduate students, professionals, and academic researchers in computer science and information technology.

This book discusses the advances of artificial intelligence and data sciences in climate change and provides the power of the climate data that is used as inputs to artificial intelligence systems. It is a good resource for researchers and professionals who work in the field of data sciences, artificial intelligence, and climate change applications.

AI-Powered IoT in the Energy Industry: Digital Technology and Sustainable Energy Systems looks at opportunities to employ cutting-edge applications of artificial intelligence (AI), the Internet of Things (IoT), and Machine Learning (ML) in designing and modeling energy and renewable energy systems. The book's main objectives are to demonstrate how big data can help with energy efficiency and demand reduction, increase the usage of renewable energy sources, and assist in transitioning from a centralized system to a distributed, efficient, and embedded energy system. Contributions cover the fundamentals of the renewable energy sector, including solar, wind, biomass, and hydrogen, as well as building services and power generation systems. Chapters also examine renewable energy property prediction methods and discuss AI and IoT prediction models for biomass thermal properties. ​Covers renewable energy sector fundamentals; Explains the application of big data in distributed energy domains; Discusses AI and IoT prediction methods and models.

This book constitutes the refereed proceedings of the 13th International Conference on Computational Logistics, ICCL 2023, held in Berlin, Germany, during September 6-8, 2023. The 32 full papers presented in this volume were carefully reviewed and selected from 71 submissions. They are grouped into the following topics: ​computational logistics; maritime shipping; vehicle routing; traffic and transport; and combinatorial optimization.

Focusing on energy, transportation, information, and economic networks and flows, Integration of Energy, Information,Transportation and Humanity uniquely examines the interconnection, interaction, and integration across these multiple sectors. It helps readers understand the correlation of energy, transportation, and information via the integration of humanity world, cyber world and physical world. It clearly explains the objectives of the integration of energy network, transportation network, information network, humanity network, as well as the integration of energy flow, information flow, material flow and value flow (4N4F); the philosophy, science, and engineering of the integration of 4N4F; the mechanism, keys and benefits of the integration of 4N4F; the carriers of the integration of 4N4F; and the framework of the integration of 4N4F. - Synthesizes the newest developments in digital technologies and digital economy - Includes case studies and examples that illustrate the application of methodologies and technologies employed - Useful for both theoretically and technically oriented researchers

The global demand for clean energy solutions the urgency of addressing climate change continue to intensify, and as such, the need for innovative approaches becomes increasingly paramount. However, navigating the complex landscape of clean energy production and sustainability presents significant challenges. Traditional methods often fall short in efficiently optimizing renewable energy systems and mitigating environmental impacts. Moreover, the integration of artificial intelligence (AI) into the energy sector remains underexplored, despite its potential to revolutionize operations and drive sustainable development. AI Applications for Clean Energy and Sustainability emerges, working to tackle these pressing issues. This comprehensive volume delves into the transformative power of AI in revolutionizing clean energy production, distribution, and management. By harnessing machine learning algorithms, data analytics, and optimization techniques, the book offers innovative solutions to enhance the efficiency, reliability, and scalability of renewable energy systems. Through real-world case studies and practical examples, it illustrates AI's potential to optimize energy infrastructure, monitor marine ecosystems, and predict climate change impacts, thereby paving the way for a more sustainable future.

Next-Generation Cyber-Physical Microgrid Systems: A Practical Guide to Communication Technologies and Resilience presents the opportunities and challenges of using communication network technology to integrate distributed generation systems into microgrids. Working their way through case studies and theoretical strategies, the global range of authors analyze the particular needs of different system structures, including DC, AC-DC and hybrid microgrids, island-bound or grid-connected systems, and case studies in wind power and photovoltaic systems. Risks arising from the communication networks are addressed in detail, with strategies covered including modelling, cyber-physical security set-ups, applications of blockchain, demand-response analyses, and the impact and mitigation of cyber-attacks. Power-electronics interfaces for the integration of these technologies are demonstrated and explained. With a wealth of real-world, practical advice for the implementation and protection of these communication strategies, Next-Generation Cyber-Physical Microgrid Systems will be a useful resource for researchers and industry professionals developing the sustainable energy systems of the future. - Provides a practical reference for resilience in the cyber-physical microgrid with distributed and renewable integration - Summarizes the opportunities and challenges arising from the implementation of communication technologies - Includes simulations, models, case studies, and test codes to maximize practical application for students and professionals