Published Online:July 2025
Product Name:The IUP Journal of Electrical & Electronics Engineering
Product Type:Article
Product Code:IJEEE010725
DOI:10.71329/IUPJEEE/2025.18.3.7-29
Author Name:Md Suzon Islam
Availability:YES
Subject/Domain:Engineering
Download Format:PDF
Pages:7-29
This study explores how artificial intelligence (AI) can improve the flexibility, efficiency, and reliability of smart grids integrated with renewable energy sources. AI-based techniques, particularly machine learning (ML), are employed for real-time forecasting, system optimization and demand management. The results demonstrate that AI implementation reduces power oscillation by 30%, increases renewable energy utilization by 25% and lowers reliance on backup fuel by 40%. Furthermore, AI-enhanced grids improve operational stability and reduce carbon emissions by up to 20%. These findings highlight AI’s role in accelerating the transition toward a sustainable, intelligent power system.
Electricity networks worldwide must incorporate renewable energy due to the increasing market demand for it. Wind and sunlight constitute renewable sources of energy, which have characteristics of intermittency owing to random changes in the force of the wind and the intensity of sunlight (Hassan et al., 2024).