Enhancing Renewable Energy Forecasting Through Artificial Intelligence: Techniques, Applications, and Future Prospects
Year: 2025
Type: article
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.
Authors: Swathi Chukkala, Sai Kumar Vadla, Raju Kumar
Institution: GITAM University
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4408409877