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Friday, July 24, 2020 | History

3 edition of Soft computing in green and renewable energy systems found in the catalog.

Soft computing in green and renewable energy systems

Kasthurirangan Gopalakrishnan

Soft computing in green and renewable energy systems

by Kasthurirangan Gopalakrishnan

  • 220 Want to read
  • 18 Currently reading

Published by Springer-Verlag in Berlin .
Written in English

    Subjects:
  • Soft computing,
  • Data processing,
  • Renewable energy sources

  • Edition Notes

    Includes bibliographical references and author index.

    StatementKasthurirangan Gopalakrishnan, Shiddhartha Kumar Khaitan, and Soteris Kalogirou, (Eds.).
    Classifications
    LC ClassificationsQA76.9.S63 S6324 2011
    The Physical Object
    Paginationxiv, 304 p. :
    Number of Pages304
    ID Numbers
    Open LibraryOL25404124M
    ISBN 103642221750
    ISBN 109783642221750
    LC Control Number2011932574

    4 Handbook on Energy-Aware and Green Computing Abstract Cloud computing is emerging as the prominent new paradigm used in distributed systems today. One of the features that makes Clouds attrac-tive is their ability to provide advanced services to users cost-e ectively by taking advantage of the economies of scale. In this, large scale Cloud. Green Computing is an echo friendly approach to the modern computing environment. It discusses about the ways of using computers in environmental friendly way. The main focus of Green computing is reducing the environmental impact of industrial processes and innovative technologies caused by the Earth’s growing population and the ways of.

    Supercomputers are changing the way scientists explore the evolution of our universe, biological systems, weather forecasting and even renewable energy. The Energy Department's National Labs have some of the most significant high performance computing resources available, including some of the fastest supercomputers in the world. Artificial Intelligence and Soft Computing for Industrial Transformation solar, and other renewable energy systems. Cutting-Edge Technology for Carbon Dioxide Capture, Utilization, and Storage Taking a new, fresh look at how the energy industry and we, as a planet, are developing our energy resources, this book looks at what is right.

    Renewable Energy Systems: Advanced Conversion Technologies and Applications - ; Soft Computing in Green and Renewable Energy Systems (Studies in Fuzziness and Soft Computing) (repost) Renewable Energy Systems: Advanced Conversion Technologies and Applications (Industrial Electronics) - Removed. Introduction Green computing, also known as Green IT, is the study and practice of environmentally responsible use of information technology. It involves such practices as energy management, the use of recyclable materials, virtualization, and the specific employee procedures and habits.


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Soft computing in green and renewable energy systems by Kasthurirangan Gopalakrishnan Download PDF EPUB FB2

Soft Computing in Green and Renewable Energy Systems provides a practical introduction to the application of soft computing techniques and hybrid intelligent systems for designing, modeling, characterizing, optimizing, forecasting, and performance prediction of green and renewable energy systems.

Research is proceeding at jet speed on renewable energy (energy derived from natural. Soft Computing in Green and Renewable Energy Systems provides a practical introduction to the application of soft computing techniques and hybrid intelligent systems for designing, modeling, characterizing, optimizing, forecasting, and performance prediction of.

ISBN: OCLC Number: Description: 1 Online-Ressource: Contents: From the content: Soft Computing Applications in Thermal Energy Systems --Use of Soft Computing Techniques in Renewable Energy Hydrogen Hybrid Systems --Soft Computing in Absorption Cooling Systems --A Comprehensive Overview of Short Term Wind Forecasting Models based on.

This textbook starts with a review of the principles of operation, modeling and control of common solar energy and wind-power generation systems before moving on to discuss grid compatibility, power quality issues and hybrid models of Solar PV and Wind Energy Conversion Systems (WECS).

Abstract. Soft computing techniques are important tools that significantly improve the performance of energy systems. This chapter reviews their many contributions to renewable energy hydrogen hybrid systems, namely those systems that consist of different technologies (photovoltaic and wind, electrolyzers, fuel cells, hydrogen storage, piping, thermal and electrical/electronic control systems Cited by: 1.

This book offers an interesting and broad catalogue of the use of state-of-the-art Soft Computing techniques in many important fields related to Renewable Energies and Energy Efficiency. Academicians and practitioners in these areas will find a complete guide about the current and future trends on the application of fuzzy sets, metaheuristics.

SAN DIEGO, Calif. – The data center industry has emerged as a leading player in the market for renewable energy, as cloud computing platforms shift to solar and wind to power theirdata center providers signed contracts for more than gigawatts of renewable power, marking a dramatic turnaround from earlier headlines critiquing the industry’s dependence upon “dirty.

He is the editor of the book Artificial Intelligence in Energy and Renewable Energy Systems, published by Nova Science Inc., co-editor of the book Soft Computing in Green and Renewable Energy Systems, published by Springer and author of the book Solar Energy Engineering: Processes and Systems, published by Academic Press of Elsevier.

Soft Computing in Green and Renewable Energy Systems (Studies in Fuzziness and Soft Computing) by Kasthurirangan Gopalakrishnan, Siddhartha Kumar Khaitan, Soteris Kalogirou.

Definition. More specifically, soft energy technologies have five defining characteristics. They rely on renewable energy resources, are diverse and designed for maximum effectiveness in particular circumstances, are flexible and relatively simple to understand, are matched to end-use needs in terms of scale, and are matched to end-use needs in terms of quality.

Energy Aware Computing: Powerful Approaches for Green System Design Paperback out of 5 stars 2 ratings See all 3 formats and editions Hide other formats and editions/5(2). In book: Soft Computing Applications for Renewable Energy and Energy Efficiency, Chapter: Evaluation of Renewable Energy Alternatives using Hesitant Fuzzy TOPSIS and Interval Type-2 Fuzzy AHP.

@book{gopalakrishnansoft, title = {Soft Computing in Green and Renewable Energy Systems}, author = {Gopalakrishnan, Kasthurirangan and Khaitan, Siddhartha Kumar and Kalogirou, Soteris}, volume = {}, year = {}, series = {Studies in Fuzziness and Soft Computing Series}, publisher = {Springer-Verlag New York Inc} }.

Green computing, green ICT as per International Federation of Global & Green ICT "IFGICT", green IT, or ICT sustainability, is the study and practice of environmentally sustainable computing or IT.

The goals of green computing are similar to green chemistry: reduce the use of hazardous materials, maximize energy efficiency during the product's lifetime, the recyclability or biodegradability.

He is the editor of the book Artificial Intelligence in Energy and Renewable Energy Systems, published by Nova Science Inc., co-editor of the book Soft Computing in Green and Renewable Energy Systems, published by Springer, editor of the book McEvoy’s Handbook of Photovoltaics, published by Academic Press of Elsevier and author of the books.

Wind energy conversion systems > Computer simulation. Soft computing. Photovoltaic power generation > Computer simulation. Soft computing. Mechanical Engineering. Engineering & Applied Sciences. Mechanical Engineering - General. Energy. Renewable and Green Energy. Energy Technology. Power Electronics, Electrical Machines and Networks.

higher penetration of renewable energy s ources especially solar, wind & hybr id systems, soft computing techniques, ener gy storage system for power quality enhancement, computer aided.

Solar PV and Wind Energy Conversion Systems: An Introduction to Theory, Modeling with MATLAB/SIMULINK, and the Role of Soft Computing Techniques / Soft Computing Techniques in Solar PV -- Wind Energy Conversion Systems -- Soft Computing Techniques in WECS -- Hybrid Energy Systems -- Grid Integration Techniques in Renewable Energy Systems.

Series Editor: Dr S. Balamurugan Scope: Artificial Intelligence and Soft Computing Techniques play an impeccable role in industrial transformation.

The topics to be covered in this book series include Artificial Intelligence, Machine Learning, Deep Learning, Neural Networks, Fuzzy Logic, Genetic Algorithms, Particle Swarm Optimization, Evolutionary Algorithms, Nature Inspired Algorithms.

Research Interests Solar thermal collectors (flat-plate, integrated and concentrating), thermosiphonic and forced circulation solar hot water systems, hybrid photovoltaic/thermal systems, computational simulation and optimization of solar systems, seawater desalination with the use of renewable energy, use of artificial intelligence systems for the performance prediction of energy and Occupation: Department Chair-Professor.

Definition. More specifically, soft energy technologies have five defining characteristics. [2] They rely on renewable energy resources, are diverse and designed for maximum effectiveness in particular circumstances, are flexible and relatively simple to understand, are matched to end-use needs in terms of scale, and are matched to end-use needs in terms of quality.Absolutely.

An energy system that doesn't leverage fundamental advances in the physical aspects of energy supply, demand and delivery probably won't have much of a chance at being truly sustainable, but information allocation is an important tool.The relatively new research field of green computing pursues energy conservation not just as a commercial advantage, (longer battery life, less weight), but as an environmental goal in itself.

Some of the green computing topics studied at Stanford include long-term trends in energy-efficient computing, resource management in large multi-core systems, and data center economics.