Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies
Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies
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Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies examines the changes in this energy generation shift, including grid stability with variability in renewable energy vs. traditional baseload energy generation, and provides solutions to current critical environmental, economic, and social issues. 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.
Format: Paperback / softback
Length: 416 pages
Publication date: 21 March 2022
Publisher: Elsevier - Health Sciences Division
Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies delves into the profound transformations occurring in the realm of energy generation, encompassing the challenges and opportunities presented by the shift towards renewable energies. This comprehensive book explores the intricate dynamics involved in this transition, including the complexities of grid stability amidst the variability of renewable energy sources compared to traditional baseload energy generation. By offering innovative solutions to pressing environmental, economic, and social issues, this text serves as a valuable resource in driving the integration of renewable energy into the grid. It examines the emerging field of artificial intelligence and machine learning, highlighting their role in developing more reliable energy generation techniques to optimize system performance and foster sustainable development.
As artificial intelligence emerges as a transformative force in the energy market, harnessing the potential of renewable energy becomes paramount. This reference provides practical guidance on the application of renewable energy alongside AI and machine learning techniques, encompassing design, modeling, and forecasting performance predictions for the optimization of renewable energy systems. It is tailored to researchers, academics, and industry professionals engaged in the fields of renewable energy, AI, machine learning, grid stability, and energy generation. By delving into the intersection of these disciplines, this book offers valuable insights and strategies for building a more sustainable and resilient energy future.
Weight: 664g
Dimension: 152 x 227 x 32 (mm)
ISBN-13: 9780323912280
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