Solar Power Forecasting Through Machine Intelligence - Couverture souple

Unni, Aparna; Channi, Harpreet Kaur

Couverture souple

ISBN 10 : 6208222486 ISBN 13 : 9786208222482

Editeur : LAP Lambert Academic Publishing, 2024

Synopsis

Solar energy is a very promising and renewable form of energy that can fulfill a substantial amount of the world's energy needs. Nevertheless, the sporadic character of renewable energy sources, caused by variables like weather patterns and time of day, presents obstacles to consistent energy production and integration into the power system. To tackle these difficulties, this study suggests an innovative method that utilizes computer vision and machine intelligence approaches to forecast and enhance the production of solar energy. The suggested approach entails the amalgamation of data-driven methods from the fields of computer vision and machine learning. Early information on climate, solar-oriented radiation, and solar-powered charger execution is gathered from various sources. PC vision calculations utilize satellite information or ground-based pictures to remove overcast cover, development, and other climatic qualities. The hour of day and season are added to visual information to deliver a full dataset. The dataset trains AI frameworks to gauge solar irradiance and energy creation.

Détails de l'édition

• Éditeur: LAP Lambert Academic Publishing
• Date d'édition: 2024
• Langue: anglais
• ISBN 10: 6208222486
• ISBN 13: 9786208222482
• Reliure: Broché
• Nombre de pages: 84
• Coordonnées du fabricant: non disponible
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