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Author : Michael Lindner
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (142 download)
Download or read book Applying Modeling, Simulation and Machine Learning for the Renewable Energy Transition written by Michael Lindner and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Krishna Kumar
Publisher : Academic Press
ISBN 13 : 0323914284
Total Pages : 418 pages
Book Rating : 4.3/5 (239 download)
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
Author : Anastasia Borochok
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (138 download)
Download or read book Modeling and Simulation of Renewable Energy Sources Using Machine Learning Techniques written by Anastasia Borochok and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the growing increase in demand for renewable energy sources, there has also been an in- crease in demand for research techniques to improve their efficiency. The cost of fossil fuel energy on the planet's C02 levels requires an alternative and cleaner energy. One of the most common and popular alternative energy are photovoltaics. This thesis will specifically focus on photovoltaic (PV) systems. Common photovoltaic systems generally lose a lot of energy in the conversion phases from solar to electrical energy. This loss of energy leads to the overall inefficiency of solar panels. Because renewable energy systems are not very efficient there are many existing methods that attempt to compensate for this deficiency. One technique to improve this inefficiency is called next generation reservoir computing (NGRC), a branch of reservoir computing (RC). NGRC is a subsection of machine learning (ML), using artificial intelligence to model human behavior and better predict data of the systems. Machine learning is a subset of artificial intelligence. Within machine learning, models are built based on existing data. NGRC differs from the older technique, RC, because it requires less computational efforts and shows promising results. The algorithm analyzes previous data and makes predictions for future outcomes. Given a specific training data set, the algorithm of the ML can analyze this data and make suggestions for future recommendations of PV operation. Based upon these predictions, PVs see an increase in power output, addressing the need and dire demand for alternative energy replacements. NGRC analyzes the system using training data sets and linear optimization; it is very efficient because it does not require large and complicated calculations. NGRC is a promising system that with greater implementation may help to better the efficiency of renewable energy like PVs.
Author : Josep M. Guerrero
Publisher : Elsevier
ISBN 13 : 044315807X
Total Pages : 315 pages
Book Rating : 4.4/5 (431 download)
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
Author : Ashutosh Kumar Dubey
Publisher : Woodhead Publishing
ISBN 13 : 0323906613
Total Pages : 408 pages
Book Rating : 4.3/5 (239 download)
Download or read book Artificial Intelligence for Renewable Energy systems written by Ashutosh Kumar Dubey and published by Woodhead Publishing. This book was released on 2022-08-01 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence for Renewable Energy Systems addresses the energy industries remarkable move from traditional power generation to a cost-effective renewable energy system, and most importantly, the paradigm shift from a market-based cost of the commodity to market-based technological advancements. Featuring recent developments and state-of-the-art applications of artificial intelligence in renewable energy systems design, the book emphasizes how AI supports effective prediction for energy generation, electric grid related line loss prediction, load forecasting, and for predicting equipment failure prevention. Looking at approaches in system modeling and performance prediction of renewable energy systems, this volume covers power generation systems, building service systems and combustion processes, exploring advances in machine learning, artificial neural networks, fuzzy logic, genetic algorithms and hybrid mechanisms. Includes real-time applications that illustrates artificial intelligence and machine learning for various renewable systems Features a templated approach that can be used to explore results, with scientific implications followed by detailed case studies Covers computational capabilities and varieties for renewable system design
Author : Rabindra Nath Shaw
Publisher : Academic Press
ISBN 13 : 0323984010
Total Pages : 248 pages
Book Rating : 4.3/5 (239 download)
Download or read book Applications of AI and IOT in Renewable Energy written by Rabindra Nath Shaw and published by Academic Press. This book was released on 2022-02-09 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applications of AI and IOT in Renewable Energy provides a future vision of unexplored areas and applications for Artificial Intelligence and Internet of Things in sustainable energy systems. The ideas presented in this book are backed up by original, unpublished technical research results covering topics like smart solar energy systems, intelligent dc motors and energy efficiency study of electric vehicles. In all these areas and more, applications of artificial intelligence methods, including artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above in hybrid systems are included. This book is designed to assist with developing low cost, smart and efficient solutions for renewable energy systems and is intended for researchers, academics and industrial communities engaged in the study and performance prediction of renewable energy systems. Includes future applications of AI and IOT in renewable energy Based on case studies to give each chapter real-life context Provides advances in renewable energy using AI and IOT with technical detail and data
Author : Dirk Deschrijver
Publisher : Mdpi AG
ISBN 13 : 9783036512075
Total Pages : 218 pages
Book Rating : 4.5/5 (12 download)
Download or read book Improving Energy Efficiency Through Data-Driven Modeling, Simulation and Optimization written by Dirk Deschrijver and published by Mdpi AG. This book was released on 2021-05-31 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: In October 2014, the EU leaders agreed upon three key targets for the year 2030: a reduction by at least 40% in greenhouse gas emissions, savings of at least 27% for renewable energy, and improvements by at least 27% in energy efficiency. The increase in computational power combined with advanced modeling and simulation tools makes it possible to derive new technological solutions that can enhance the energy efficiency of systems and that can reduce the ecological footprint. This book compiles 10 novel research works from a Special Issue that was focused on data-driven approaches, machine learning, or artificial intelligence for the modeling, simulation, and optimization of energy systems.
Author : Ravinesh Deo
Publisher : Elsevier
ISBN 13 : 0128177721
Total Pages : 552 pages
Book Rating : 4.1/5 (281 download)
Download or read book Predictive Modelling for Energy Management and Power Systems Engineering written by Ravinesh Deo and published by Elsevier. This book was released on 2020-10-14 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predictive Modeling for Energy Management and Power Systems Engineering introduces readers to the cutting-edge use of big data and large computational infrastructures in energy demand estimation and power management systems. The book supports engineers and scientists who seek to become familiar with advanced optimization techniques for power systems designs, optimization techniques and algorithms for consumer power management, and potential applications of machine learning and artificial intelligence in this field. The book provides modeling theory in an easy-to-read format, verified with on-site models and case studies for specific geographic regions and complex consumer markets. Presents advanced optimization techniques to improve existing energy demand system Provides data-analytic models and their practical relevance in proven case studies Explores novel developments in machine-learning and artificial intelligence applied in energy management Provides modeling theory in an easy-to-read format
Author : Mohammadali Ahmadi
Publisher : Elsevier
ISBN 13 : 0443240116
Total Pages : 517 pages
Book Rating : 4.4/5 (432 download)
Download or read book Artificial Intelligence for a More Sustainable Oil and Gas Industry and the Energy Transition written by Mohammadali Ahmadi and published by Elsevier. This book was released on 2024-08-01 with total page 517 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence for a More Sustainable Oil and Gas Industry and the Energy Transition: Case Studies and Code Examples presents a package for academic researchers and industries working on water resources and carbon capture and storage. This book contains fundamental knowledge on artificial intelligence related to oil and gas sustainability and the industry’s pivot to support the energy transition and provides practical applications through case studies and coding flowcharts, addressing gaps and questions raised by academic and industrial partners, including energy engineers, geologists, and environmental scientists. This timely publication provides fundamental and extensive information on advanced AI applications geared to support sustainability and the energy transition for the oil and gas industry. Reviews the use and applications of AI in energy transition of the oil and gas sectors Provides fundamental knowledge and academic background of artificial intelligence, including practical applications with real-world examples and coding flowcharts Showcases the successful implementation of AI in the industry (including geothermal energy)
Author : Ahmad Taher Azar
Publisher : Academic Press
ISBN 13 : 0128203986
Total Pages : 734 pages
Book Rating : 4.1/5 (282 download)
Download or read book Renewable Energy Systems written by Ahmad Taher Azar and published by Academic Press. This book was released on 2021-09-09 with total page 734 pages. Available in PDF, EPUB and Kindle. Book excerpt: Renewable Energy Systems: Modelling, Optimization and Control aims to cross-pollinate recent advances in the study of renewable energy control systems by bringing together diverse scientific breakthroughs on the modeling, control and optimization of renewable energy systems by leading researchers. The book brings together the most comprehensive collection of modeling, control theorems and optimization techniques to help solve many scientific issues for researchers in renewable energy and control engineering. Many multidisciplinary applications are discussed, including new fundamentals, modeling, analysis, design, realization and experimental results. The book also covers new circuits and systems to help researchers solve many nonlinear problems. This book fills the gaps between different interdisciplinary applications, ranging from mathematical concepts, modeling, and analysis, up to the realization and experimental work. Covers modeling, control theorems and optimization techniques which will solve many scientific issues for researchers in renewable energy Discusses many multidisciplinary applications with new fundamentals, modeling, analysis, design, realization and experimental results Includes new circuits and systems, helping researchers solve many nonlinear problems
Author : Naoui, Mohamed
Publisher : IGI Global
ISBN 13 :
Total Pages : 357 pages
Book Rating : 4.3/5 (693 download)
Download or read book Modeling, Analysis, and Control of Smart Energy Systems written by Naoui, Mohamed and published by IGI Global. This book was released on 2024-08-08 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: The increasing demand for cleaner and more intelligent energy solutions poses a challenge that resonates across academic, engineering, and policymaking spheres. The complexity of integrating renewable energy sources, energy storage solutions, and advanced communication technologies demands a comprehensive understanding, rigorous analysis, and innovative control strategies. The academic community, in particular, seeks a guiding light through this intricate maze of evolving energy dynamics. Modeling, Analysis, and Control of Smart Energy Systems is a groundbreaking publication that offers more than theoretical exploration; it is a roadmap equipped with the knowledge and tools required to shape the future of energy systems. From laying conceptual foundations to unraveling real-world case studies, the book seamlessly bridges the gap between theory and application. Its comprehensive coverage of mathematical modeling, dynamic system analysis, intelligent control strategies, and the integration of renewable energy sources positions it as an authoritative reference for researchers, engineers, and policymakers alike.
Author : Pinaki Pratim Acharjya
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.3/5 (693 download)
Download or read book Machine Learning and Computer Vision for Renewable Energy written by Pinaki Pratim Acharjya and published by . This book was released on 2024 with total page 0 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 and Computer Vision for Renewable Energy positions itself as a catalyst for this change. The book not only addresses the immediate concerns of the energy sector but also details how to achieve a more sustainable future. By emphasizing breakthroughs in CV and AI, the objective is clear: to drive societal progress through research, innovation, and technological advancements in the domain of renewable energy. Academic researchers, professors, college students, and business professionals focused on the intersection of digital transformation and renewable energy will find this book to be an indispensable guide to navigating the challenges and opportunities that lie ahead. With a diverse array of recommended topics, this book stands as a testament to the evolving landscape of AI and computer vision, shaping a sustainable energy future for generations to come.
Author : Mohamed Abdelaziz Mohamed
Publisher : Springer
ISBN 13 : 3319647954
Total Pages : 91 pages
Book Rating : 4.3/5 (196 download)
Download or read book Modeling and Simulation of Smart Grid Integrated with Hybrid Renewable Energy Systems written by Mohamed Abdelaziz Mohamed and published by Springer. This book was released on 2017-08-03 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive definition of smart grids and their benefits, and compares smart and traditional grids. It also introduces a design methodology for stand-alone hybrid renewable energy system with and without applying the smart grid concepts for comparison purposes. It discusses using renewable energy power plants to feed loads in remote areas as well as in central power plants connected to electric utilities. Smart grid concepts used in the design of the hybrid renewable power systems can reduce the size of components, which can be translated to a reduction in the cost of generated energy. The proposed hybrid renewable energy system includes wind, photovoltaic, battery, and diesel, and is used initially to feed certain loads, covering the load required completely. The book introduces a novel methodology taking the smart grid concept into account by dividing the loads into high and low priority parts. The high priority part should be supplied at any generated conditions. However, the low priority loads can be shifted to the time when the generated energy from renewable energy sources is greater than the high priority loads requirements. The results show that the use of this smart grid concept reduces the component size and the cost of generated energy compared to that without dividing the loads. The book also describes the use of smart optimization techniques like particle swarm optimization (PSO) and genetic algorithm (GA) to optimally design the hybrid renewable energy system. This book provides an excellent background to renewable energy sources, optimal sizing and locating of hybrid renewable energy sources, the best optimization methodologies for sizing and designing the components of hybrid renewable energy systems, and offers insights into using smart grid concepts in the system’s design and sizing. It also helps readers understand the dispatch methodology and how to connect the system’s different components, their modeling, and the cost analysis of the system.
Author : Ala A. Hussein
Publisher : Materials Research Forum LLC
ISBN 13 : 1644903202
Total Pages : 400 pages
Book Rating : 4.6/5 (449 download)
Download or read book Renewable Energy: Generation and Application written by Ala A. Hussein and published by Materials Research Forum LLC. This book was released on 2024-08-15 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book covers the current status of renewable energy technology, such as solar, wind, hydro and geothermal power engineering and biomass conversion. It focusses on technical challenges and potential future developments in electricity generation. electrical vehicles, heating and cooling, industrial processes and rural electrification. Keywords: Solar Energy, Wind Energy, Wind Farms. Hydropower, Hydroelectric Dams, Geothermal Energy, Biomass Energy, Agricultural Residues, Organic Waste, Electricity Transportation, Global Energy Systems.
Author : Neeraj Priyadarshi
Publisher : John Wiley & Sons
ISBN 13 : 1119786274
Total Pages : 484 pages
Book Rating : 4.1/5 (197 download)
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.
Author : Fausto Cavallaro
Publisher : Springer Science & Business Media
ISBN 13 : 1447151437
Total Pages : 438 pages
Book Rating : 4.4/5 (471 download)
Download or read book Assessment and Simulation Tools for Sustainable Energy Systems written by Fausto Cavallaro and published by Springer Science & Business Media. This book was released on 2013-08-13 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, the concept of energy has been revised and a new model based on the principle of sustainability has become more and more pervasive. The appraisal of energy technologies and projects is complex and uncertain as the related decision making has to encompass environmental, technical, economic and social factors and information sources. The scientific procedure of assessment has a vital role as it can supply the right tools to evaluate the actual situation and make realistic forecasts of the effects and outcomes of any actions undertaken. Assessment and Simulation Tools for Sustainable Energy Systems offers reviews of the main assessment and simulation methods used for effective energy assessment. Divided across three sections, Assessment and Simulation Tools for Sustainable Energy Systems develops the reader’s ability to select suitable tools to support decision making and implementation of sustainable energy projects. The first is dedicated to the analysis of theoretical foundations and applications of multi-criteria decision making. This is followed by chapters concentrating on the theory and practice of fuzzy inference, neural nets and algorithms genetics. Finally, simulation methods such as Monte Carlo analysis, mathematical programming and others are detailed. This comprehensive illustration of these tools and their application makes Assessment and Simulation Tools for Sustainable Energy Systems a key guide for researchers, scientists, managers, politicians and industry professionals developing the field of sustainable energy systems. It may also prompt further advancements in soft computing and simulation issues for students and researchers.
Author : Amit Kumar Yadav
Publisher : Elsevier
ISBN 13 : 0443134839
Total Pages : 0 pages
Book Rating : 4.4/5 (431 download)
Download or read book Intelligent Data Analytics for Solar Energy Prediction and Forecasting written by Amit Kumar Yadav and published by Elsevier. This book was released on 2023-11-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent Data Analytics for Solar Energy Prediction and Forecasting: Advances in Resource Assessment and PV Systems Optimization explores the utilization of advanced neural networks, machine learning and data analytics techniques for solar radiation prediction, solar energy forecasting, installation and maximum power generation. The book addresses relevant input variable selection, solar resource assessment, tilt angle calculation, and electrical characteristics of PV modules, including detailed methods, coding, modeling and experimental analysis of PV power generation under outdoor conditions. It will be of interest to researchers, scientists and advanced students across solar energy, renewables, electrical engineering, AI, machine learning, computer science, information technology and engineers. In addition, R&D professionals and other industry personnel with an interest in applications of AI, machine learning, and data analytics within solar energy and energy systems will find this book to be a welcomed resource. Presents novel intelligent techniques with step-by-step coverage for improved optimum tilt angle calculation for the installation of photovoltaic systems Provides coding and modeling for data-driven techniques in prediction and forecasting Covers intelligent data-driven techniques for solar energy forecasting and prediction
