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

Author : Yuekuan Zhou
Publisher : Elsevier
ISBN 13 : 0443131783
Total Pages : 302 pages
Book Rating : 4.4/5 (431 download)

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Book Synopsis Advances in Digitalization and Machine Learning for Integrated Building-Transportation Energy Systems by : Yuekuan Zhou

Download or read book Advances in Digitalization and Machine Learning for Integrated Building-Transportation Energy Systems written by Yuekuan Zhou and published by Elsevier. This book was released on 2023-11-20 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : Acharjya, Pinaki Pratim
Publisher : IGI Global
ISBN 13 :
Total Pages : 351 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Machine Learning and Computer Vision for Renewable Energy by : Acharjya, Pinaki Pratim

Download or read book Machine Learning and Computer Vision for Renewable Energy written by Acharjya, Pinaki Pratim and published by IGI Global. This book was released on 2024-05-01 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Machine Learning for Energy Systems

Author : Denis Sidorov
Publisher : MDPI
ISBN 13 : 3039433822
Total Pages : 272 pages
Book Rating : 4.0/5 (394 download)

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Book Synopsis Machine Learning for Energy Systems by : Denis Sidorov

Download or read book Machine Learning for Energy Systems written by Denis Sidorov and published by MDPI. This book was released on 2020-12-08 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume deals with recent advances in and applications of computational intelligence and advanced machine learning methods in power systems, heating and cooling systems, and gas transportation systems. The optimal coordinated dispatch of the multi-energy microgrids with renewable generation and storage control using advanced numerical methods is discussed. Forecasting models are designed for electrical insulator faults, the health of the battery, electrical insulator faults, wind speed and power, PV output power and transformer oil test parameters. The loads balance algorithm for an offshore wind farm is proposed. The information security problems in the energy internet are analyzed and attacked using information transmission contemporary models, based on blockchain technology. This book will be of interest, not only to electrical engineers, but also to applied mathematicians who are looking for novel challenging problems to focus on.

Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies

Author : Krishna Kumar
Publisher : Academic Press
ISBN 13 : 0323914284
Total Pages : 418 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies by : Krishna Kumar

Download or read book Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies written by Krishna Kumar and published by Academic Press. This book was released on 2022-03-18 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies analyzes the changes in this energy generation shift, including issues of grid stability with variability in renewable energy vs. traditional baseload energy generation. Providing solutions to current critical environmental, economic and social issues, this book comprises various complex nonlinear interactions among different parameters to drive the integration of renewable energy into the grid. It considers how artificial intelligence and machine learning techniques are being developed to produce more reliable energy generation to optimize system performance and provide sustainable development. As the use of artificial intelligence to revolutionize the energy market and harness the potential of renewable energy is essential, this reference provides practical guidance on the application of renewable energy with AI, along with machine learning techniques and capabilities in design, modeling and for forecasting performance predictions for the optimization of renewable energy systems. It is targeted at researchers, academicians and industry professionals working in the field of renewable energy, AI, machine learning, grid Stability and energy generation. Covers the best-performing methods and approaches for designing renewable energy systems with AI integration in a real-time environment Gives advanced techniques for monitoring current technologies and how to efficiently utilize the energy grid spectrum Addresses the advanced field of renewable generation, from research, impact and idea development of new applications

Smart Buildings Digitalization

Author : O.V. Gnana Swathika
Publisher : CRC Press
ISBN 13 : 1000537943
Total Pages : 421 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Smart Buildings Digitalization by : O.V. Gnana Swathika

Download or read book Smart Buildings Digitalization written by O.V. Gnana Swathika and published by CRC Press. This book was released on 2022-02-24 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses various artificial intelligence and machine learning applications concerning smart buildings. It includes how renewable energy sources are integrated into smart buildings using suitable power electronic devices. The deployment of advanced technologies with monitoring, protection, and energy management features is included, along with a case study on automation. Overall, the focus is on architecture and related applications, such as power distribution, microgrids, photovoltaic systems, and renewable energy aspects. The chapters define smart building concepts and their related benefits. FEATURES Discusses various aspects of the role of the Internet of things (IoT) and machine learning in smart buildings Explains pertinent system architecture and focuses on power generation and distribution Covers power-enabling technologies for smart cities Includes photovoltaic system-integrated smart buildings This book is aimed at graduate students, researchers, and professionals in building systems engineering, architectural engineering, and electrical engineering.

Machine Learning for Energy Systems

Author : Denis N. Sidorov
Publisher :
ISBN 13 : 9783039433834
Total Pages : 272 pages
Book Rating : 4.4/5 (338 download)

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Book Synopsis Machine Learning for Energy Systems by : Denis N. Sidorov

Download or read book Machine Learning for Energy Systems written by Denis N. Sidorov and published by . This book was released on 2020 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume deals with recent advances in and applications of computational intelligence and advanced machine learning methods in power systems, heating and cooling systems, and gas transportation systems. The optimal coordinated dispatch of the multi-energy microgrids with renewable generation and storage control using advanced numerical methods is discussed. Forecasting models are designed for electrical insulator faults, the health of the battery, electrical insulator faults, wind speed and power, PV output power and transformer oil test parameters. The loads balance algorithm for an offshore wind farm is proposed. The information security problems in the energy internet are analyzed and attacked using information transmission contemporary models, based on blockchain technology. This book will be of interest, not only to electrical engineers, but also to applied mathematicians who are looking for novel challenging problems to focus on.

Advances in Smart Energy Systems

Author : Biplab Das
Publisher : Springer Nature
ISBN 13 : 9811924120
Total Pages : 300 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Advances in Smart Energy Systems by : Biplab Das

Download or read book Advances in Smart Energy Systems written by Biplab Das and published by Springer Nature. This book was released on 2022-08-31 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses smart computing techniques which offer an effective solution for investigating and modeling the stochastic behavior of renewable energy generation, operation of grid-connected renewable energy systems, and smart decision-making among alternatives. It also discusses applications of soft computing techniques to make an intelligent decision for optimum use of suitable alternatives which gives an upper hand compared to conventional systems. It includes upgradation of the existing system by embedding of machine intelligence. The authors present combination of use of neutral networks, fuzzy systems, and genetic algorithms which are illustrated in several applications including forecasting, security, verification, diagnostics of a specific fault, efficiency optimization, etc. Smart energy systems integrate a holistic approach in diverse sectors including electricity, thermal comfort, power industry, transportation. It allows affordable and sustainable solutions to solve the future energy demands with suitable alternatives. Thus, contributions regarding integration of the machine intelligence with the energy system, for efficient collection and effective utilization of the available energy sources, are useful for further advanced studies.

Intelligent Learning Approaches for Renewable and Sustainable Energy

Author : Josep M. Guerrero
Publisher : Elsevier
ISBN 13 : 044315807X
Total Pages : 315 pages
Book Rating : 4.4/5 (431 download)

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Book Synopsis Intelligent Learning Approaches for Renewable and Sustainable Energy by : Josep M. Guerrero

Download or read book Intelligent Learning Approaches for Renewable and Sustainable Energy written by Josep M. Guerrero and published by Elsevier. This book was released on 2024-02-21 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent Learning Approaches for Renewable and Sustainable Energy provides a practical, systematic overview of the application of advanced intelligent control techniques, adaptive techniques, machine learning algorithms, and predictive control in renewable and sustainable energy.The book begins by introducing the intelligent learning approaches, and the roles of artificial intelligence and machine learning in terms of energy and sustainability, grid transformation, large-scale integration of renewable energy, and variability and flexibility of renewable sources. The second section of the book provides detailed coverage of intelligent learning techniques as applied to key areas of renewable and sustainable energy, including forecasting, supply and demand, integration, energy management, and optimization, supported by case studies, figures, schematics, and references.This is a useful resource for researchers, scientists, advanced students, energy engineers, R&D professionals, and other industrial personnel with an interest in sustainable energy and integration of renewable energy sources, energy systems, energy engineering, machine learning, and artificial intelligence. Explores cutting-edge intelligent techniques and their implications for future energy systems development Opens the door to a range of applications across forecasting, supply and demand, energy management, optimization, and more Includes a range of case studies that provide insights into the challenges and solutions in real-world applications

Artificial Intelligence for Renewable Energy Systems

Author : Ajay Kumar Vyas
Publisher : John Wiley & Sons
ISBN 13 : 1119761697
Total Pages : 276 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Artificial Intelligence for Renewable Energy Systems by : Ajay Kumar Vyas

Download or read book Artificial Intelligence for Renewable Energy Systems written by Ajay Kumar Vyas and published by John Wiley & Sons. This book was released on 2022-03-02 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY SYSTEMS Renewable energy systems, including solar, wind, biodiesel, hybrid energy, and other relevant types, have numerous advantages compared to their conventional counterparts. This book presents the application of machine learning and deep learning techniques for renewable energy system modeling, forecasting, and optimization for efficient system design. Due to the importance of renewable energy in today’s world, this book was designed to enhance the reader’s knowledge based on current developments in the field. For instance, the extraction and selection of machine learning algorithms for renewable energy systems, forecasting of wind and solar radiation are featured in the book. Also highlighted are intelligent data, renewable energy informatics systems based on supervisory control and data acquisition (SCADA); and intelligent condition monitoring of solar and wind energy systems. Moreover, an AI-based system for real-time decision-making for renewable energy systems is presented; and also demonstrated is the prediction of energy consumption in green buildings using machine learning. The chapter authors also provide both experimental and real datasets with great potential in the renewable energy sector, which apply machine learning (ML) and deep learning (DL) algorithms that will be helpful for economic and environmental forecasting of the renewable energy business. Audience The primary target audience includes research scholars, industry engineers, and graduate students working in renewable energy, electrical engineering, machine learning, information & communication technology.

AI-Powered IoT in the Energy Industry

Author : S. Vijayalakshmi
Publisher : Springer Nature
ISBN 13 : 3031150449
Total Pages : 318 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis AI-Powered IoT in the Energy Industry by : S. Vijayalakshmi

Download or read book AI-Powered IoT in the Energy Industry written by S. Vijayalakshmi and published by Springer Nature. This book was released on 2023-04-05 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Advanced Computational Techniques for Renewable Energy Systems

Author : Mustapha Hatti
Publisher : Springer
ISBN 13 : 9783031212154
Total Pages : 0 pages
Book Rating : 4.2/5 (121 download)

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Book Synopsis Advanced Computational Techniques for Renewable Energy Systems by : Mustapha Hatti

Download or read book Advanced Computational Techniques for Renewable Energy Systems written by Mustapha Hatti and published by Springer. This book was released on 2023-02-15 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, one hundred selected articles, in which the technology and science elite share, contribute to technology development, collaborate and evolve the latest cutting-edge technologies, open ecosystem resources, new innovative computing solutions, hands-on labs and tutorials, networking and community building, to ensure better integration of artificial intelligence into renewable energy systems. Innovation in computing continues at a growing pace. The key to success in this area is not only hardware, but also the ability to leverage rapid advances in artificial intelligence (including machine learning and deep learning), data analytics, data streaming, and cloud computing, which go hand in hand with intensive research activity on the underlying computational methods. The chapters in this book are organized into thematic sections on: advanced computing techniques; artificial intelligence; smart and sustainable cities; renewable energy systems; materials in renewable energy; smart energy efficiency; smart cities applications: recent developments and new trends; online, supervision of renewable energy platforms; predictive control in renewable systems; smart embedded systems for photovoltaic applications.

AI and IOT in Renewable Energy

Author : Rabindra Nath Shaw
Publisher : Springer Nature
ISBN 13 : 9811610118
Total Pages : 109 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis AI and IOT in Renewable Energy by : Rabindra Nath Shaw

Download or read book AI and IOT in Renewable Energy written by Rabindra Nath Shaw and published by Springer Nature. This book was released on 2021-05-12 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest research on applications of artificial intelligence and the Internet of Things in renewable energy systems. Advanced renewable energy systems must necessarily involve the latest technology like artificial intelligence and Internet of Things to develop low cost, smart and efficient solutions. Intelligence allows the system to optimize the power, thereby making it a power efficient system; whereas, Internet of Things makes the system independent of wire and flexibility in operation. As a result, intelligent and IOT paradigms are finding increasing applications in the study of renewable energy systems. This book presents advanced applications of artificial intelligence and the internet of things in renewable energy systems development. It covers such topics as solar energy systems, electric vehicles etc. In all these areas applications of artificial intelligence methods such as artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above, called hybrid systems, are included. The book is intended for a wide audience ranging from the undergraduate level up to the research academic and industrial communities engaged in the study and performance prediction of renewable energy systems.

Enabling technologies and business models for energy communities

Author : Alessandro Burgio
Publisher : Frontiers Media SA
ISBN 13 : 2832543243
Total Pages : 211 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Enabling technologies and business models for energy communities by : Alessandro Burgio

Download or read book Enabling technologies and business models for energy communities written by Alessandro Burgio and published by Frontiers Media SA. This book was released on 2024-01-19 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Construction 4.0

Author : Marco Casini
Publisher : Woodhead Publishing
ISBN 13 : 0128218037
Total Pages : 696 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Construction 4.0 by : Marco Casini

Download or read book Construction 4.0 written by Marco Casini and published by Woodhead Publishing. This book was released on 2021-11-24 with total page 696 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Advances in Artificial Intelligence for Renewable Energy Systems and Energy Autonomy

Author : Mukhdeep Singh Manshahia
Publisher : Springer Nature
ISBN 13 : 3031264967
Total Pages : 302 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Advances in Artificial Intelligence for Renewable Energy Systems and Energy Autonomy by : Mukhdeep Singh Manshahia

Download or read book Advances in Artificial Intelligence for Renewable Energy Systems and Energy Autonomy written by Mukhdeep Singh Manshahia and published by Springer Nature. This book was released on 2023-06-14 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with emerging research that explores the theoretical and practical aspects of implementing new and innovative artificial intelligence (AI) techniques for renewable energy systems. The contributions offer broad coverage on economic and promotion policies of renewable energy and energy-efficiency technologies, the emerging fields of neuro-computational models and simulations under uncertainty (such as fuzzy-based computational models and fuzzy trace theory), evolutionary computation, metaheuristics, machine learning applications, advanced optimization, and stochastic models. This book is a pivotal reference for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research in emerging perspectives in artificial intelligence, renewable energy systems, and energy autonomy.

Artificial Intelligence Techniques for a Scalable Energy Transition

Author : Moamar Sayed-Mouchaweh
Publisher : Springer Nature
ISBN 13 : 3030427269
Total Pages : 383 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Artificial Intelligence Techniques for a Scalable Energy Transition by : Moamar Sayed-Mouchaweh

Download or read book Artificial Intelligence Techniques for a Scalable Energy Transition written by Moamar Sayed-Mouchaweh and published by Springer Nature. This book was released on 2020-06-19 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents research in artificial techniques using intelligence for energy transition, outlining several applications including production systems, energy production, energy distribution, energy management, renewable energy production, cyber security, industry 4.0 and internet of things etc. The book goes beyond standard application by placing a specific focus on the use of AI techniques to address the challenges related to the different applications and topics of energy transition. The contributions are classified according to the market and actor interactions (service providers, manufacturers, customers, integrators, utilities etc.), to the SG architecture model (physical layer, infrastructure layer, and business layer), to the digital twin of SG (business model, operational model, fault/transient model, and asset model), and to the application domain (demand side management, load monitoring, micro grids, energy consulting (residents, utilities), energy saving, dynamic pricing revenue management and smart meters, etc.).

Intelligent Renewable Energy Systems

Author : Neeraj Priyadarshi
Publisher : John Wiley & Sons
ISBN 13 : 1119786274
Total Pages : 484 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Intelligent Renewable Energy Systems by : Neeraj Priyadarshi

Download or read book Intelligent Renewable Energy Systems written by Neeraj Priyadarshi and published by John Wiley & Sons. This book was released on 2022-01-19 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: INTELLIGENT RENEWABLE ENERGY SYSTEMS This collection of papers on artificial intelligence and other methods for improving renewable energy systems, written by industry experts, is a reflection of the state of the art, a must-have for engineers, maintenance personnel, students, and anyone else wanting to stay abreast with current energy systems concepts and technology. Renewable energy is one of the most important subjects being studied, researched, and advanced in today’s world. From a macro level, like the stabilization of the entire world’s economy, to the micro level, like how you are going to heat or cool your home tonight, energy, specifically renewable energy, is on the forefront of the discussion. This book illustrates modelling, simulation, design and control of renewable energy systems employed with recent artificial intelligence (AI) and optimization techniques for performance enhancement. Current renewable energy sources have less power conversion efficiency because of its intermittent and fluctuating behavior. Therefore, in this regard, the recent AI and optimization techniques are able to deal with data ambiguity, noise, imprecision, and nonlinear behavior of renewable energy sources more efficiently compared to classical soft computing techniques. This book provides an extensive analysis of recent state of the art AI and optimization techniques applied to green energy systems. Subsequently, researchers, industry persons, undergraduate and graduate students involved in green energy will greatly benefit from this comprehensive volume, a must-have for any library. Audience Engineers, scientists, managers, researchers, students, and other professionals working in the field of renewable energy.