Advances in Digitalization and Machine Learning for Integrated Building-Transportation Energy Systems

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Advances in Digitalization and Machine Learning for Integrated Building-Transportation Energy Systems

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  • 製本 Paperback:紙装版/ペーパーバック版／ページ数 300 p.
  • 言語 ENG
  • 商品コード 9780443131776
  • DDC分類 621.31

Full Description

Advances in Digitalization and Machine Learning for Integrated Building-Transportation Energy Systems examines the combined impact of buildings and transportation systems on energy demand and use. With a strong focus on AI and machine learning approaches, the book comprehensively discusses each part of the energy lifecycle, considering source, grid, demand, storage, and usage. Opening with an introduction to smart buildings and intelligent transportation systems, the book presents the fundamentals of AI and its application in renewable energy sources, alongside the latest technological advances.

Other topics presented include building occupants' behavior and vehicle driving schedule with demand prediction and analysis, hybrid energy storages in buildings with AI, smart grid with energy digitalization, and prosumer-based P2P energy trading. The book concludes with discussions on blockchain technologies, IoT in smart grid operation, and the application of big data and cloud computing in integrated smart building-transportation energy systems. This title provides critical information to students, researchers, and engineers wanting to understand, design, and implement flexible energy systems to meet the rising demand in electricity.

Contents

1. Introduction to smart buildings and intelligent transportations with Artificial Intelligent and Digitalization Technology2. ML and AI Distributed Renewable Energy sources, technologies, perspectives, and challenges3. Building occupants' behavior and vehicle driving schedule with demand prediction and analysis4. Spatiotemporal energy sharing with new energy vehicles and Human-Machine Interaction5. Integrated Energy Flexible Building and E-Mobility with Demand-side management and model predictive control6. Electrification and hydrogenation in integrated building-transportation systems for sustainability7. Hybrid Energy storages in buildings with AI8. Smart grid with energy digitalization9. AI-powered 'source-grid-load-storage' optimization in multi-energy systems10. Prosumer-based P2P energy trading with advanced energy pricing mechanism11. Blockchain technologies for secure and tamper-proof in energy trading12. Energy Resilience, Robustness and Reliability in smart district energy systems13. Application of internet of energy things and digitalization in smart grid operation14. Application of Big Data and cloud computing for Integrated Smart Building-Transportation Energy Systems development15. Social and economic analysis of integrated Building-Transportation Energy Systems

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