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

Advances in Digitalization and Machine Learning for Integrated Building-Transportation Energy Systems PDF Author: Yuekuan Zhou
Publisher: Elsevier
ISBN: 0443131783
Category : Computers
Languages : en
Pages : 302

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Book 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 life cycle, 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. A smart and flexible energy system is essential for reaching Net Zero whilst keeping energy bills affordable. 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. - Introduces spatiotemporal energy sharing with new energy vehicles and human-machine interactions - Discusses the potential for electrification and hydrogenation in integrated building-transportation systems for sustainable development - Highlights key topics related to traditional energy consumers, including peer-to-peer energy trading and cost-benefit business models

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

Advances in Digitalization and Machine Learning for Integrated Building-Transportation Energy Systems PDF Author: Yuekuan Zhou
Publisher: Elsevier
ISBN: 0443131783
Category : Computers
Languages : en
Pages : 302

Get Book Here

Book 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 life cycle, 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. A smart and flexible energy system is essential for reaching Net Zero whilst keeping energy bills affordable. 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. - Introduces spatiotemporal energy sharing with new energy vehicles and human-machine interactions - Discusses the potential for electrification and hydrogenation in integrated building-transportation systems for sustainable development - Highlights key topics related to traditional energy consumers, including peer-to-peer energy trading and cost-benefit business models

Machine Learning and Computer Vision for Renewable Energy

Machine Learning and Computer Vision for Renewable Energy PDF Author: Acharjya, Pinaki Pratim
Publisher: IGI Global
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 351

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Book Description
As the world grapples with the urgent need for sustainable energy solutions, the limitations of traditional approaches to renewable energy forecasting become increasingly evident. The demand for more accurate predictions in net load forecasting, line loss predictions, and the seamless integration of hybrid solar and battery storage systems is more critical than ever. In response to this challenge, advanced Artificial Intelligence (AI) techniques are emerging as a solution, promising to revolutionize the renewable energy landscape. Machine Learning and Computer Vision for Renewable Energy presents a deep exploration of AI modeling, analysis, performance prediction, and control approaches dedicated to overcoming the pressing issues in renewable energy systems. Transitioning from the complexities of energy prediction to the promise of advanced technology, the book sets its sights on the game-changing potential of computer vision (CV) in the realm of renewable energy. Amidst the struggle to enhance sustainability across industries, CV technology emerges as a powerful ally, collecting invaluable data from digital photos and videos. This data proves instrumental in achieving better energy management, predicting factors affecting renewable energy, and optimizing overall sustainability. Readers, including researchers, academicians, and students, will find themselves immersed in a comprehensive understanding of the AI approaches and CV methodologies that hold the key to resolving the challenges faced by renewable energy systems.

Energy Systems Engineering Exam Essentials

Energy Systems Engineering Exam Essentials PDF Author: Cybellium
Publisher: Cybellium Ltd
ISBN: 1836794495
Category : Study Aids
Languages : en
Pages : 226

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Book Description
Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com

Enabling technologies and business models for energy communities

Enabling technologies and business models for energy communities PDF Author: Alessandro Burgio
Publisher: Frontiers Media SA
ISBN: 2832543243
Category : Technology & Engineering
Languages : en
Pages : 211

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Book Description


Data-driven Analytics for Sustainable Buildings and Cities

Data-driven Analytics for Sustainable Buildings and Cities PDF Author: Xingxing Zhang
Publisher: Springer Nature
ISBN: 9811627789
Category : Social Science
Languages : en
Pages : 446

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Book Description
This book explores the interdisciplinary and transdisciplinary fields of energy systems, occupant behavior, thermal comfort, air quality and economic modelling across levels of building, communities and cities, through various data analytical approaches. It highlights the complex interplay of heating/cooling, ventilation and power systems in different processes, such as design, renovation and operation, for buildings, communities and cities. Methods from classical statistics, machine learning and artificial intelligence are applied into analyses for different building/urban components and systems. Knowledge from this book assists to accelerate sustainability of the society, which would contribute to a prospective improvement through data analysis in the liveability of both built and urban environment. This book targets a broad readership with specific experience and knowledge in data analysis, energy system, built environment and urban planning. As such, it appeals to researchers, graduate students, data scientists, engineers, consultants, urban scientists, investors and policymakers, with interests in energy flexibility, building/city resilience and climate neutrality.

Construction 4.0

Construction 4.0 PDF Author: Marco Casini
Publisher: Woodhead Publishing
ISBN: 0128218037
Category : Technology & Engineering
Languages : en
Pages : 696

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Book Description
Developments in data acquisition technologies, digital information and analysis, automated construction processes, and advanced materials and products have finally started to move the construction industry - traditionally reluctant to innovation and slow in adopting new technologies - toward a new era. Massive changes are occurring because of the possibilities created by Building information modeling, Extended reality, Internet of Things, Artificial intelligence and Machine Learning, Big data, Nanotechnology, 3D printing, and other advanced technologies, which are strongly interconnected and are driving the capabilities for much more efficient construction at scale. Construction 4.0: Advanced Technology, Tools and Materials for the Digital Transformation of the Construction Industry provides readers with a state-of-the-art review of the ongoing digital transformation of the sector within the new 4.0 framework, presenting a thorough investigation of the emerging trends, technologies, and strategies in the fields of smart building design, construction, and operation and providing a comprehensive guideline on how to exploit the new possibilities offered by the digital revolution. It will be an essential reference resource for academic researchers, material scientists and civil engineers, undergraduate and graduate students, and other professionals working in the field of smart ecoefficient construction and cutting-edge technologies applied to construction. - Provides an overview of the Construction 4.0 framework to address the global challenges of the buildingsector in the 21st century and an in-depth analysis of the most advanced digital technologies and systems forthe operation and maintenance of infrastructure, real estate, and other built assets - Covers major innovations across the value chain, including building design, fabrication, construction, operationand maintenance, and end-of-life - Illustrates the most advanced digital tools and methods to support the building design activity, includinggenerative design, virtual reality, and digital fabrication - Presents a thorough review of the most advanced construction materials, building methods, and techniquesfor a new connected and automated construction model - Explores the digital transformation for smart energy buildings and their integration with emerging smartgrids and smart cities - Reflects upon major findings and identifies emerging market opportunities for the whole AECO sector

Computer Vision and Machine Intelligence for Renewable Energy Systems

Computer Vision and Machine Intelligence for Renewable Energy Systems PDF Author: Ashutosh Kumar Dubey
Publisher: Elsevier
ISBN: 0443289484
Category : Technology & Engineering
Languages : en
Pages : 389

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Book Description
Computer Vision and Machine Intelligence for Renewable Energy Systems offers a practical, systemic guide to the use of computer vision as an innovative tool to support renewable energy integration.This book equips readers with a variety of essential tools and applications: Part I outlines the fundamentals of computer vision and its unique benefits in renewable energy system models compared to traditional machine intelligence: minimal computing power needs, speed, and accuracy even with partial data. Part II breaks down specific techniques, including those for predictive modeling, performance prediction, market models, and mitigation measures. Part III offers case studies and applications to a wide range of renewable energy sources, and finally the future possibilities of the technology are considered. The very first book in Elsevier's cutting-edge new series Advances in Intelligent Energy Systems, Computer Vision and Machine Intelligence for Renewable Energy Systems provides engineers and renewable energy researchers with a holistic, clear introduction to this promising strategy for control and reliability in renewable energy grids. - Provides a sorely needed primer on the opportunities of computer vision techniques for renewable energy systems - Builds knowledge and tools in a systematic manner, from fundamentals to advanced applications - Includes dedicated chapters with case studies and applications for each sustainable energy source

Encyclopedia of Renewable Energy, Sustainability and the Environment

Encyclopedia of Renewable Energy, Sustainability and the Environment PDF Author:
Publisher: Elsevier
ISBN: 0323939414
Category : Science
Languages : en
Pages : 4061

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Book Description
Encyclopedia of Renewable Energy, Sustainability and the Environment, Four Volume Set comprehensively covers all renewable energy resources, including wind, solar, hydro, biomass, geothermal energy, and nuclear power, to name a few. In addition to covering the breadth of renewable energy resources at a fundamental level, this encyclopedia delves into the utilization and ideal applications of each resource and assesses them from environmental, economic, and policy standpoints. This book will serve as an ideal introduction to any renewable energy source for students, while also allowing them to learn about a topic in more depth and explore related topics, all in a single resource.Instructors, researchers, and industry professionals will also benefit from this comprehensive reference. - Covers all renewable energy technologies in one comprehensive resource - Details renewable energies' processes, from production to utilization in a single encyclopedia - Organizes topics into concise, consistently formatted chapters, perfect for readers who are new to the field - Assesses economic challenges faced to implement each type of renewable energy - Addresses the challenges of replacing fossil fuels with renewables and covers the environmental impacts of each renewable energy

Artificial Intelligence and Its Practical Applications in the Digital Economy

Artificial Intelligence and Its Practical Applications in the Digital Economy PDF Author: Yahya Mohamed Elhadj
Publisher: Springer Nature
ISBN: 3031714261
Category :
Languages : en
Pages : 284

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Book Description


Digital Twins

Digital Twins PDF Author: Yogini Borole
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110778866
Category : Business & Economics
Languages : en
Pages : 256

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Book Description