Applications of date-driven artificial intelligence in integrated energy systems PDF Download
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Author: Qiuye Sun
Publisher: Frontiers Media SA
ISBN: 2832510256
Category : Technology & Engineering
Languages : en
Pages : 119
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Book Description
Author: Qiuye Sun
Publisher: Frontiers Media SA
ISBN: 2832510256
Category : Technology & Engineering
Languages : en
Pages : 119
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Book Description
Author: B Rajanarayan Prusty
Publisher:
ISBN: 9781032472065
Category : Computers
Languages : en
Pages : 0
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Book Description
This book provides a comprehensive understanding of how intelligent data-driven techniques can be used for modelling, controlling, and optimizing various power and energy applications. It aims to develop multiple data-driven models for forecasting renewable energy sources and to interpret the benefits of these techniques in line with first-principles modelling approaches. By doing so, the book aims to stimulate deep insights into computational intelligence approaches in data-driven models and to promote their potential applications in the power and energy sectors. Its key features include: an exclusive section on essential preprocessing approaches for the data-driven model a detailed overview of data-driven model applications to power system planning and operational activities specific focus on developing forecasting models for renewable generations such as solar PV and wind power, and showcasing the judicious amalgamation of allied mathematical treatments such as optimization and fractional calculus in data-driven model-based frameworks This book presents novel concepts for applying data-driven models, mainly in the power and energy sectors, and is intended for graduate students, industry professionals, research, and academic personnel.
Author: Rathishchandra R. Gatti
Publisher: John Wiley & Sons
ISBN: 111984200X
Category : Computers
Languages : en
Pages : 374
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Book Description
SELF-POWERED CYBER PHYSICAL SYSTEMS This cutting-edge new volume provides a comprehensive exploration of emerging technologies and trends in energy management, self-powered devices, and cyber-physical systems, offering valuable insights into the future of autonomous systems and addressing the urgent need for energy-efficient solutions in a world that is increasingly data-driven and sensor-rich. This book is an attempt to aim at a very futuristic vision of achieving self-powered cyber-physical systems by applying a multitude of current technologies such as ULP electronics, thin film electronics, ULP transducers, autonomous wireless sensor networks using energy harvesters at the component level and energy efficient clean energy for powering data centers and machines at the system level. This is the need of the hour for cyber-physical systems since data requires energy when it is stored, transmitted, or converted to other forms. Cyber-physical systems will become energy hungry since the industry trend is towards ubiquitous computing with massive deployment of sensors and actuators. This is evident in using blockchain technologies such as Bitcoin or running epochs for artificial intelligence (AI) applications. Hence, there is a need for research to understand energy patterns and distribution in cyber-physical systems and adopt new technologies to transcend to self-powered cyber-physical systems. This book explores the recent trends in energy management, self-powered devices, and methods in the cyber-physical world. Written and edited by a team of experts in the field, this book tackles a multitude of subjects related to cyber physical systems (CPSs), including self-powered sensory transducers, ambient energy harvesting for wireless sensor networks, actuator methods and non-contact sensing equipment for soft robots, alternative optimization strategies for DGDCs to improve task distribution and provider profits, wireless power transfer methods, machine learning algorithms for CPS and IoT applications, integration of renewables, electric vehicles (EVs), smart grids, RES micro-grid and EV systems for effective load matching, self-powered car cyber-physical systems, anonymous routing and intrusion detection systems for VANET security, data-driven pavement distress prediction methods, the impact of autonomous vehicles on industries and the auto insurance market, Intelligent transportation systems and associated security concerns, digital twin prototypes and their automotive applications, farming robotics for CPS farming, self-powered CPS in smart cities, self-powered CPS in healthcare and biomedical devices, cyber-security considerations, societal impact and ethical concerns, and advances in human-machine interfaces and explore the integration of self-powered CPS in industrial automation. Whether for the veteran engineer or student, this volume is a must-have for any library.
Author: Miltiadis D. Lytras
Publisher: MDPI
ISBN: 303928889X
Category : Technology & Engineering
Languages : en
Pages : 258
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Book Description
Energy has been a crucial element for human beings and sustainable development. The issues of global warming and non-green energy have yet to be resolved. This book is a collection of twelve articles that provide strong evidence for the success of artificial intelligence deployment in energy research, particularly research devoted to non-intrusive load monitoring, network, and grid, as well as other emerging topics. The presented artificial intelligence algorithms may provide insight into how to apply similar approaches, subject to fine-tuning and customization, to other unexplored energy research. The ultimate goal is to fully apply artificial intelligence to the energy sector. This book may serve as a guide for professionals, researchers, and data scientists—namely, how to share opinions and exchange ideas so as to facilitate a better fusion of energy, academic, and industry research, and improve in the quality of people's daily life activities.
Author: Sasan Azad
Publisher: Springer
ISBN: 9783031693571
Category : Technology & Engineering
Languages : en
Pages : 0
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Book Description
This book covers the practical application of AI-based methods in modern power systems. The complexity of current power system operations has dramatically increased due to the higher penetration of renewable energy sources and power electronic components. Therefore, providing efficient techniques is essential for secure and clean power system operation. This book focuses on the data-driven operation of the digitalized power system using machine language (ML). First, the basics of power system operation and control are presented, covering various areas of system control and operation. Next, significant advances in modern power systems and their corresponding challenges are discussed, and artificial intelligence (AI)-powered techniques, specifically machine learning, are introduced to address these issues. The book also explores AI-powered applications in the operation of power systems. These applications include various aspects of the data-driven process in both situational awareness and control areas. They are presented as practical examples indicating the implementation of an ML-based method to solve operational problems. Artificial Intelligence in the Operation and Control of Digitalized Power Systems is a valuable guide for students, researchers, and practicing engineers to AI-based techniques and real-world applications in power systems.
Author: Narjes Abbasabadi
Publisher: John Wiley & Sons
ISBN: 1394172060
Category : Architecture
Languages : en
Pages : 308
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Book Description
ARTIFICIAL INTELLIGENCE IN PERFORMANCE-DRIVEN DESIGN A definitive, interdisciplinary reference to using artificial intelligence technology and data-driven methodologies for sustainable design Artificial Intelligence in Performance-Driven Design: Theories, Methods, and Tools explores the application of artificial intelligence (AI), specifically machine learning (ML), for performance modeling within the built environment. This work develops the theoretical foundations and methodological frameworks for utilizing AI/ML, with an emphasis on multi-scale modeling encompassing energy flows, environmental quality, and human systems. The book examines relevant practices, case studies, and computational tools that harness AI’s capabilities in modeling frameworks, enhancing the efficiency, accuracy, and integration of physics-based simulation, optimization, and automation processes. Furthermore, it highlights the integration of intelligent systems and digital twins throughout the lifecycle of the built environment, to enhance our understanding and management of these complex environments. This book also: Incorporates emerging technologies into practical ideas to improve performance analysis and sustainable design Presents data-driven methodologies and technologies that integrate into modeling and design platforms Shares valuable insights and tools for developing decarbonization pathways in urban buildings Includes contributions from expert researchers and educators across a range of related fields Artificial Intelligence in Performance-Driven Design is ideal for architects, engineers, planners, and researchers involved in sustainable design and the built environment. It’s also of interest to students of architecture, building science and technology, urban design and planning, environmental engineering, and computer science and engineering.
Author: Krishna Kumar
Publisher: Academic Press
ISBN: 0323914284
Category : Science
Languages : en
Pages : 418
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Book Description
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
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
Author: Jeng-Shyang Pan
Publisher: Springer
ISBN: 364240846X
Category : Computers
Languages : en
Pages : 710
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Book Description
This volume constitutes the proceedings of the 8th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2013, held in Salamanca, Spain, in September 2013. The 68 papers published in this volume were carefully reviewed and selected from 218 submissions. They are organized in topical sessions on Agents and Multi Agents Systems; HAIS Applications; Classification and Cluster Analysis; Data Mining and Knowledge Discovery; Video and Image Analysis; Bio-inspired Models and Evolutionary Computation; Learning Algorithms; Systems, MAN, and Cybernetics; Hybrid Intelligent Systems for Data Mining and Applications; Metaheuristics for Combinatorial Optimization and Modelling Complex Systems.
Author: Bhartiya, Shivam
Publisher: IGI Global
ISBN:
Category : Business & Economics
Languages : en
Pages : 333
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Book Description
In the rapidly changing landscape of global tourism and community dynamics, a pressing challenge emerges — the delicate balance between gastronomy tourism, community development, and social impact. As communities grapple with the consequences of unchecked tourism, the need for a sustainable approach becomes vital. Gastronomic Sustainability Solutions for Community and Tourism Resilience is a groundbreaking exploration illuminating the intricate interplay between food, culture, and socio-economic aspects. This comprehensive work identifies the challenges and presents innovative solutions that transcend traditional paradigms, ensuring the long-term well-being of both host communities and the ever-evolving world of travel. Gastronomic Sustainability Solutions for Community and Tourism Resilience is a transformative narrative revealing sustainable gastronomy practices' power. As communities seek avenues for economic growth and cultural preservation, this book charts a course toward genuine, mutually beneficial travel experiences. Through compelling case studies and theoretical insights, readers are guided through a journey showcasing how gastronomy tourism's convergence can revitalize local economies, celebrate cultural heritage, and foster cross-cultural understanding. The book proposes a paradigm shift in how we approach travel and provides tangible strategies for community leaders, businesses, and individuals to embrace a more sustainable and responsible future.
