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Author: Vikas Khare
Publisher: Butterworth-Heinemann
ISBN: 0128189053
Category : Science
Languages : en
Pages : 371
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Book Description
Ocean Energy Modeling and Simulation with Big Data: Computational Intelligence for System Optimization and Grid Integration offers the fundamental and practical aspects of big data solutions applied to ocean and offshore energy systems. The book explores techniques for assessment of tidal, wave and offshore wind energy systems. It presents the use of data mining software to simulate systems and Hadoop technology to evaluate control systems. The use of Map Reduce algorithms in systems optimization is examined, along with the application of NoSQL in systems management. Actual data collection through web-based applications and social networks is discussed, along with practical applications of recommendations. - Introduces computational methods for processing and analyzing data to predict ocean energy system production, assess their efficiency, and ensure their reliable connection to power grids - Covers data processing solutions like Hadoop, NoSQL, Map Reduce and Lambda, discussing their applications in ocean energy for system design and optimization - Provides practical exercises that demonstrate the concepts explored in each chapter
Author: Vikas Khare
Publisher: Butterworth-Heinemann
ISBN: 0128189053
Category : Science
Languages : en
Pages : 371
Get Book Here
Book Description
Ocean Energy Modeling and Simulation with Big Data: Computational Intelligence for System Optimization and Grid Integration offers the fundamental and practical aspects of big data solutions applied to ocean and offshore energy systems. The book explores techniques for assessment of tidal, wave and offshore wind energy systems. It presents the use of data mining software to simulate systems and Hadoop technology to evaluate control systems. The use of Map Reduce algorithms in systems optimization is examined, along with the application of NoSQL in systems management. Actual data collection through web-based applications and social networks is discussed, along with practical applications of recommendations. - Introduces computational methods for processing and analyzing data to predict ocean energy system production, assess their efficiency, and ensure their reliable connection to power grids - Covers data processing solutions like Hadoop, NoSQL, Map Reduce and Lambda, discussing their applications in ocean energy for system design and optimization - Provides practical exercises that demonstrate the concepts explored in each chapter
Author: Pawan Kumar
Publisher: CRC Press
ISBN: 1000379620
Category : Computers
Languages : en
Pages : 248
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Book Description
The Internet of Energy (IoE), with the integration of advanced information and communication technologies (ICT), has led to a transformation of traditional networks to smart systems. Internet of Energy Handbook provides updated knowledge in the field of energy management with an Internet of Things (IoT) perspective. Features Explains the technological developments for energy management leading to a reduction in energy consumption through topics like smart energy systems, smart sensors, communication, techniques, and utilization Includes dedicated sections covering varied aspects related to renewable sources of energy, power distribution, and generation Incorporates energy efficiency, optimization, and sensor technologies Covers multidisciplinary aspects in computational intelligence and IoT Discusses building energy management aspects including temperature, humidity, the number of persons involved, and light intensity This handbook is aimed at graduate students, researchers, and professionals interested in power systems, IoT, smart grids, electrical engineering, and transmission.
Author: S. Vijayalakshmi
Publisher: Springer Nature
ISBN: 3031150449
Category : Technology & Engineering
Languages : en
Pages : 318
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Book Description
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.
Author: Ahmad Taher Azar
Publisher: Academic Press
ISBN: 0323859917
Category : Technology & Engineering
Languages : en
Pages : 762
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Book Description
Design, Analysis and Applications of Renewable Energy Systems covers recent advancements in the study of renewable energy control systems by bringing together diverse scientific breakthroughs on the modeling, control and optimization of renewable energy systems as conveyed by leading energy systems engineering researchers. The book focuses on present novel solutions for many problems in the field, covering modeling, control theorems and the optimization techniques that will help solve many scientific issues for researchers. Multidisciplinary applications are also discussed, along with their fundamentals, modeling, analysis, design, realization and experimental results. This book fills the gaps between different interdisciplinary applications, ranging from mathematical concepts, modeling, and analysis, up to the realization and experimental work. - Presents some of the latest innovative approaches to renewable energy systems from the point-of-view of dynamic modeling, system analysis, optimization, control and circuit design - Focuses on advances related to optimization techniques for renewable energy and forecasting using machine learning methods - Includes new circuits and systems, helping researchers solve many nonlinear problems
Author: Mariano Martin
Publisher: Elsevier
ISBN: 0128243252
Category : Technology & Engineering
Languages : en
Pages : 685
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Book Description
Sustainable Design for Renewable Processes: Principles and Case Studies covers the basic technologies to collect and process renewable resources and raw materials and transform them into useful products. Starting with basic principles on process analysis, integration and optimization that also addresses challenges, the book then discusses applied principles using a number of examples and case studies that cover biomass, waste, solar, water and wind as resources, along with a set of technologies including gasification, pyrolysis, hydrolysis, digestion, fermentation, solar thermal, solar photovoltaics, electrolysis, energy storage, etc. The book includes examples, exercises and models using Python, Julia, MATLAB, GAMS, EXCEL, CHEMCAD or ASPEN. This book shows students the challenges posed by renewable-based processes by presenting fundamentals, case studies and step-by-step analyses of renewable resources. Hence, this is an ideal and comprehensive reference for Masters and PhD students, engineers and designers. - Addresses the fundamentals and applications of renewable energy process design for all major resources, including biomass, solar, wind, geothermal, waste and water - Provides detailed case studies, step-by-step instructions, and guidance for each renewable energy technology - Presents models and simulations for a wide variety of platforms, including state-of-the-art and open access platforms in addition to well-known commercial software
Author: Zhihua Zhang
Publisher: Elsevier
ISBN: 0128187034
Category : Science
Languages : en
Pages : 344
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Book Description
Climate change mechanisms, impacts, risks, mitigation, adaption, and governance are widely recognized as the biggest, most interconnected problem facing humanity. Big Data Mining for Climate Change addresses one of the fundamental issues facing scientists of climate or the environment: how to manage the vast amount of information available and analyse it. The resulting integrated and interdisciplinary big data mining approaches are emerging, partially with the help of the United Nation's big data climate challenge, some of which are recommended widely as new approaches for climate change research. Big Data Mining for Climate Change delivers a rich understanding of climate-related big data techniques and highlights how to navigate huge amount of climate data and resources available using big data applications. It guides future directions and will boom big-data-driven researches on modeling, diagnosing and predicting climate change and mitigating related impacts. This book mainly focuses on climate network models, deep learning techniques for climate dynamics, automated feature extraction of climate variability, and sparsification of big climate data. It also includes a revelatory exploration of big-data-driven low-carbon economy and management. Its content provides cutting-edge knowledge for scientists and advanced students studying climate change from various disciplines, including atmospheric, oceanic and environmental sciences; geography, ecology, energy, economics, management, engineering, and public policy.
Author: Joanna Kołodziej
Publisher: Springer
ISBN: 3030162729
Category : Computers
Languages : en
Pages : 364
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Book Description
This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications.
Author: Saurabh Mittal
Publisher: Springer
ISBN: 3319612646
Category : Computers
Languages : en
Pages : 376
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Book Description
This invaluable text/reference reviews the state of the art in simulation-based approaches across a wide range of different disciplines, and provides evidence of using simulation-based approaches to advance these disciplines. Highlighting the benefits that simulation can bring to any field, the volume presents case studies by the leading experts from such diverse domains as the life sciences, engineering, architecture, arts, and social sciences. Topics and features: includes review questions at the end of every chapter; provides a broad overview of the evolution of the concept of simulation, stressing its importance across numerous sectors and disciplines; addresses the role of simulation in engineering design, and emphasizes the benefits of integrating simulation into the systems engineering paradigm; explains the relation of simulation with Cyber-Physical Systems and the Internet of Things, and describes a simulation infrastructure for complex adaptive systems; investigates how simulation is used in the Software Design Life Cycle to assess complex solutions, and examines the use of simulation in architectural design; reviews the function and purpose of simulation within the context of the scientific method, and its contribution to healthcare and health education training; discusses the position of simulation in research in the social sciences, and describes the simulation of service systems for simulation-based enterprise management; describes the role of simulation in learning and education, as well as in in military training. With its near-exhaustive coverage of disciplines, this comprehensive collection is essential reading for all researchers, practitioners and students seeking insights into the use of various modeling paradigms and the need for robust simulation infrastructure to advance their field into a computational future.
Author: Kang Li
Publisher: Springer
ISBN: 9811063648
Category : Computers
Languages : en
Pages : 824
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Book Description
The three-volume set CCIS 761, CCIS 762, and CCIS 763 constitutes the thoroughly refereed proceedings of the International Conference on Life System Modeling and Simulation, LSMS 2017, and of the International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2017, held in Nanjing, China, in September 2017. The 208 revised full papers presented were carefully reviewed and selected from over 625 submissions. The papers of this volume are organized in topical sections on: Biomedical Signal Processing; Computational Methods in Organism Modeling; Medical Apparatus and Clinical Applications; Bionics Control Methods, Algorithms and Apparatus; Modeling and Simulation of Life Systems; Data Driven Analysis; Image and Video Processing; Advanced Fuzzy and Neural Network Theory and Algorithms; Advanced Evolutionary Methods and Applications; Advanced Machine Learning Methods and Applications; Intelligent Modeling, Monitoring, and Control of Complex Nonlinear Systems; Advanced Methods for Networked Systems; Control and Analysis of Transportation Systems; Advanced Sliding Mode Control and Applications; Advanced Analysis of New Materials and Devices; Computational Intelligence in Utilization of Clean and Renewable Energy Resources; Intelligent Methods for Energy Saving and Pollution Reduction; Intelligent Methods in Developing Electric Vehicles, Engines and Equipment; Intelligent Computing and Control in Power Systems; Modeling, Simulation and Control in Smart Grid and Microgrid; Optimization Methods; Computational Methods for Sustainable Environment.
Author: Michel Fathi
Publisher: Springer Nature
ISBN: 3030979407
Category : Business & Economics
Languages : en
Pages : 3382
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Book Description
This handbook analyzes and develops methods and models to optimize solutions for energy access (for industry and the general world population alike) in terms of reliability and sustainability. With a focus on improving the performance of energy systems, it brings together state-of-the-art research on reliability enhancement, intelligent development, simulation and optimization, as well as sustainable development of energy systems. It helps energy stakeholders and professionals learn the methodologies needed to improve the reliability of energy supply-and-demand systems, achieve more efficient long-term operations, deal with uncertainties in energy systems, and reduce energy emissions. Highlighting novel models and their applications from leading experts in this important area, this book will appeal to researchers, students, and engineers in the various domains of smart energy systems and encourage them to pursue research and development in this exciting and highly relevant field.
