Artificial Intelligence Techniques For A Scalable Energy Transition
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Artificial Intelligence Techniques For A Scalable Energy Transition
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Author : Moamar Sayed-Mouchaweh
language : en
Publisher: Springer Nature
Release Date : 2020-06-19
Artificial Intelligence Techniques For A Scalable Energy Transition written by Moamar Sayed-Mouchaweh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-19 with Technology & Engineering categories.
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.).
Advances In Artificial Intelligence For Renewable Energy Systems And Energy Autonomy
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Author : Mukhdeep Singh Manshahia
language : en
Publisher: Springer Nature
Release Date : 2023-06-14
Advances In Artificial Intelligence For Renewable Energy Systems And Energy Autonomy written by Mukhdeep Singh Manshahia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-14 with Technology & Engineering categories.
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.
Introduction To Ai Techniques For Renewable Energy System
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Author : Suman Lata Tripathi
language : en
Publisher: CRC Press
Release Date : 2021-11-25
Introduction To Ai Techniques For Renewable Energy System written by Suman Lata Tripathi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-25 with Technology & Engineering categories.
Introduction to AI techniques for Renewable Energy System Artificial Intelligence (AI) techniques play an essential role in modeling, analysis, and prediction of the performance and control of renewable energy. The algorithms used to model, control, or predict performances of the energy systems are complicated, involving differential equations, enormous computing power, and time requirements. Instead of complex rules and mathematical routines, AI techniques can learn critical information patterns within a multidimensional information domain. Design, control, and operation of renewable energy systems require a long-term series of meteorological data such as solar radiation, temperature, or wind data. Such long-term measurements are often non-existent for most of the interest locations or, wherever they are available, they suffer from several shortcomings, like inferior quality of data, and in-sufficient long series. The book focuses on AI techniques to overcome these problems. It summarizes commonly used AI methodologies in renewal energy, with a particular emphasis on neural networks, fuzzy logic, and genetic algorithms. It outlines selected AI applications for renewable energy. In particular, it discusses methods using the AI approach for prediction and modeling of solar radiation, seizing, performances, and controls of the solar photovoltaic (PV) systems. Features Focuses on a significant area of concern to develop a foundation for the implementation of renewable energy system with intelligent techniques Showcases how researchers working on renewable energy systems can correlate their work with intelligent and machine learning approaches Highlights international standards for intelligent renewable energy systems design, reliability, and maintenance Provides insights on solar cell, biofuels, wind, and other renewable energy systems design and characterization, including the equipment for smart energy systems This book, which includes real-life examples, is aimed at undergraduate and graduate students and academicians studying AI techniques used in renewal energy systems.
Artificial Intelligence For Renewable Energy Systems
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Author : Ajay Kumar Vyas
language : en
Publisher: John Wiley & Sons
Release Date : 2022-03-02
Artificial Intelligence For Renewable Energy Systems written by Ajay Kumar Vyas and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-02 with Computers categories.
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.
Intelligent Renewable Energy Systems
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Author : Neeraj Priyadarshi
language : en
Publisher: John Wiley & Sons
Release Date : 2022-01-19
Intelligent Renewable Energy Systems written by Neeraj Priyadarshi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-19 with Computers categories.
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.
Machine Learning Applications For Intelligent Energy Management
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Author : Haris Doukas
language : en
Publisher: Springer
Release Date : 2024-02-02
Machine Learning Applications For Intelligent Energy Management written by Haris Doukas and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-02 with Technology & Engineering categories.
As carbon dioxide (CO2) emissions and other greenhouse gases constantly rise and constitute the main contributor to climate change, temperature rise and global warming, artificial intelligence, big data, Internet of things, and blockchain technologies are enlisted to help enforce energy transition and transform the entire energy sector. The book at hand presents state-of-the-art developments in artificial intelligence-empowered analytics of energy data and artificial intelligence-empowered application development. Topics covered include a presentation of the various stakeholders in the energy sector and their corresponding required analytic services, such as state-of-the-art machine learning, artificial intelligence, and optimization models and algorithms tailored for a series of demanding energy problems and aiming at providing optimal solutions under specific constraints. Professors, researchers, scientists, engineers, and students in energy sector-related disciplines are expected to be inspired and benefit from this book, along with readers from other disciplines wishing to learn more about this exciting new field of research.
Sustainable Developments By Artificial Intelligence And Machine Learning For Renewable Energies
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Author : Krishna Kumar
language : en
Publisher: Academic Press
Release Date : 2022-03-18
Sustainable Developments By Artificial Intelligence And Machine Learning For Renewable Energies written by Krishna Kumar and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-18 with Science categories.
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
Explainable Ai Within The Digital Transformation And Cyber Physical Systems
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Author : Moamar Sayed-Mouchaweh
language : en
Publisher: Springer Nature
Release Date : 2021-10-30
Explainable Ai Within The Digital Transformation And Cyber Physical Systems written by Moamar Sayed-Mouchaweh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-30 with Technology & Engineering categories.
This book presents Explainable Artificial Intelligence (XAI), which aims at producing explainable models that enable human users to understand and appropriately trust the obtained results. The authors discuss the challenges involved in making machine learning-based AI explainable. Firstly, that the explanations must be adapted to different stakeholders (end-users, policy makers, industries, utilities etc.) with different levels of technical knowledge (managers, engineers, technicians, etc.) in different application domains. Secondly, that it is important to develop an evaluation framework and standards in order to measure the effectiveness of the provided explanations at the human and the technical levels. This book gathers research contributions aiming at the development and/or the use of XAI techniques in order to address the aforementioned challenges in different applications such as healthcare, finance, cybersecurity, and document summarization. It allows highlighting the benefits and requirements of using explainable models in different application domains in order to provide guidance to readers to select the most adapted models to their specified problem and conditions. Includes recent developments of the use of Explainable Artificial Intelligence (XAI) in order to address the challenges of digital transition and cyber-physical systems; Provides a textual scientific description of the use of XAI in order to address the challenges of digital transition and cyber-physical systems; Presents examples and case studies in order to increase transparency and understanding of the methodological concepts.
Intelligent Learning Approaches For Renewable And Sustainable Energy
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Author : Josep M. Guerrero
language : en
Publisher: Elsevier
Release Date : 2024-02-21
Intelligent Learning Approaches For Renewable And Sustainable Energy written by Josep M. Guerrero and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-21 with Computers categories.
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
Toward Artificial General Intelligence
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Author : Victor Hugo C. de Albuquerque
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2023-11-06
Toward Artificial General Intelligence written by Victor Hugo C. de Albuquerque and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-06 with Computers categories.