Computer Vision and Machine Intelligence for Renewable Energy Systems

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: Fundamentals

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: Techniques

Breaks down specific techniques, including those for predictive modeling, performance prediction, market models, and mitigation measures.

Part III: Case Studies and Future

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