Computer Vision and Machine Intelligence for Renewable Energy Systems

Computer Vision and Machine Intelligence for Renewable Energy Systems
Author :
Publisher : Elsevier
Total Pages : 389
Release :
ISBN-10 : 9780443289484
ISBN-13 : 0443289484
Rating : 4/5 (484 Downloads)

Book Synopsis Computer Vision and Machine Intelligence for Renewable Energy Systems by : Ashutosh Kumar Dubey

Download or read book Computer Vision and Machine Intelligence for Renewable Energy Systems written by Ashutosh Kumar Dubey and published by Elsevier. This book was released on 2024-09-20 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer Vision and Machine Intelligence for Renewable Energy Systems offers a practical, systemic guide to the use of computer vision as an innovative tool to support renewable energy integration.This book equips readers with a variety of essential tools and applications: Part I outlines the fundamentals of computer vision and its unique benefits in renewable energy system models compared to traditional machine intelligence: minimal computing power needs, speed, and accuracy even with partial data. Part II breaks down specific techniques, including those for predictive modeling, performance prediction, market models, and mitigation measures. Part III offers case studies and applications to a wide range of renewable energy sources, and finally the future possibilities of the technology are considered. The very first book in Elsevier's cutting-edge new series Advances in Intelligent Energy Systems, Computer Vision and Machine Intelligence for Renewable Energy Systems provides engineers and renewable energy researchers with a holistic, clear introduction to this promising strategy for control and reliability in renewable energy grids. - Provides a sorely needed primer on the opportunities of computer vision techniques for renewable energy systems - Builds knowledge and tools in a systematic manner, from fundamentals to advanced applications - Includes dedicated chapters with case studies and applications for each sustainable energy source


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