AI-Based Performance Analysis of Renewable Energy Systems for Sustainable Power Generation
G Vidhya,
M Suchithra,
Santhosh G,
M Anupama
The growing demand for clean and reliable energy has accelerated the adoption of renewable energy
systems such as solar photovoltaic and wind power technologies. However, the inherent variability
of renewable resources poses significant challenges in performance prediction, system optimization,
and reliable power generation. This study presents an artificial intelligence–based framework for
performance analysis of renewable energy systems aimed at supporting sustainable power generation.
Operational and environmental data are utilized to develop machine learning models capable of
capturing complex, nonlinear relationships between system inputs and energy output. The AI-based
approach is evaluated against conventional analytical methods using performance indicators such
as power output, efficiency, prediction accuracy, and response time. The results demonstrate that AIdriven
models significantly improve prediction accuracy, reduce analysis time, and enhance system
performance assessment under varying operating conditions. The findings highlight the potential of
artificial intelligence to improve operational efficiency, support intelligent energy management, and
strengthen the integration of renewable energy systems into sustainable power networks.
