A Study of Computer Vision, Deep Learning, and Machine Learning Techniques for Forecasting Solar Power and Renewable Energy-Reference-Cited by-同舟云学术

A Study of Computer Vision, Deep Learning, and Machine Learning Techniques for Forecasting Solar Power and Renewable Energy

Published:2024-05-17 Issue: Volume: Page:66-84
ISSN:2326-9162
Container-title:Advances in Environmental Engineering and Green Technologies
language:
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Author:

Majumder Jayeeta¹,Acharjya Pinaki Pratim¹^ORCID,Barman Subhabrata¹,Koley Santanu¹^ORCID

Affiliation:

1. Haldia Institute of Technology, India

Abstract

Utilising renewable energy sources is becoming more popular as a way to mitigate the effects of climate change and global warming. In an effort to make renewable energy more predictable, numerous prediction techniques have been developed. The objectives of this study are best illustrated by this chapter, which aims to provide a review and analysis of machine-learning and computer vision techniques in renewable solar energy projections. In addition to machine-learning and computer vision techniques for renewable solar energy projections, this chapter also focuses on the objective to deliver an optimized academic outcome, potentially necessary for the development of new solar energy fields. This could significantly contribute to the amplified usage of solar energy, which is a sustainable and cleaner energy source.

Publisher

IGI Global

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