Enhancing Renewable Energy Forecasting Through Artificial Intelligence: Techniques, Applications, and Future Prospects

Artificial Intelligence (AI) application for renewable energy forecasting marks an important step for sustainable development, proving especially valuable for government sectors working toward better energy management.The study investigates how AI and machine learning can forecast solar and wind energy outputs.Key studies reviewed in this literature reveal progress and obstacles faced within this field.The methodology section details the AI methods used for energy forecasting and highlights their precision and performance.The findings show that AI can improve renewable energy reliability, which supports energy stability and informs policy development.The promising results show that obstacles relating to data quality and algorithmic transparency remain unresolved.The conclusion addresses the existing limitations and recommends future research directions while promoting the joint development of AI models to improve their incorporation into national energy systems.The research provides insights for policymakers and researchers regarding AI's ability to transform energy systems toward sustainable solutions.

Authors

Publication Details

Journal
International Journal of Research Publication and Reviews
Published
2025-03-01
DOI
https://doi.org/10.55248/gengpi.6.0225.1034
Primary Topic
Energy Load and Power Forecasting
Type
article
Field-Weighted Citation Impact
0.00
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article

Enhancing Renewable Energy Forecasting Through Artificial Intelligence: Techniques, Applications, and Future Prospects

Raju Kumar, Swathi Chukkala, Sai Kumar Vadla
International Journal of Research Publication and Reviews
Energy Load and Power Forecasting
article

Enhancing Renewable Energy Forecasting Through Artificial Intelligence: Techniques, Applications, and Future Prospects

Raju Kumar, Swathi Chukkala, Sai Kumar Vadla
article en

Abstract

Artificial Intelligence (AI) application for renewable energy forecasting marks an important step for sustainable development, proving especially valuable for government sectors working toward better energy management.The study investigates how AI and machine learning can forecast solar and wind energy outputs.Key studies reviewed in this literature reveal progress and obstacles faced within this field.The methodology section details the AI methods used for energy forecasting and highlights their precision and performance.The findings show that AI can improve renewable energy reliability, which supports energy stability and informs policy development.The promising results show that obstacles relating to data quality and algorithmic transparency remain unresolved.The conclusion addresses the existing limitations and recommends future research directions while promoting the joint development of AI models to improve their incorporation into national energy systems.The research provides insights for policymakers and researchers regarding AI's ability to transform energy systems toward sustainable solutions.

International Journal of Research Publication and ReviewsVol. 6(2)
Affordable and clean energy
Openalex Percentile: Top 96%
Energy Load and Power Forecasting
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Enhancing Renewable Energy Forecasting Through Artificial Intelligence: Techniques, Applications, and Future Prospects — Raju Kumar, Swathi Chukkala, et al. · International Journal of Research Publication and Reviews (2025) | TGRS Research Map | TGRS