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Analysis Study Research Paper | Renewable Energy | Volume 15 Issue 4, April 2026 | Pages: 966 - 967 | India
Renewable Energy: A Sustainable Future - The Impact of Artificial Intelligence
Abstract: The global transition toward renewable energy is a cornerstone of climate change mitigation and long-term energy security. However, the inherent intermittency of solar and wind sources poses significant challenges to grid stability. This paper evaluates the transformative role of Artificial Intelligence (AI) in optimizing renewable energy systems, focusing on forecasting, grid management, and predictive maintenance. Utilizing global capacity data from IRENA and the IEA (2020-2025), we analyze the performance of a Deep Learning-based Long Short-Term Memory (LSTM) model for solar power prediction. Our results demonstrate that AI integration enhances forecasting accuracy by up to 25% and improves overall grid efficiency by 15%, while reducing operational maintenance costs by approximately 30%. The paper concludes that AI-driven digitalization is the primary catalyst for achieving 2050 net-zero targets.
Keywords: Renewable energy, artificial intelligence, sustainability, LSTM networks, smart grid, energy forecasting
How to Cite?: Rajiv Pandey, Rohit Pradhan, Bharti Shrivas, "Renewable Energy: A Sustainable Future - The Impact of Artificial Intelligence", Volume 15 Issue 4, April 2026, International Journal of Science and Research (IJSR), Pages: 966-967, https://www.ijsr.net/getabstract.php?paperid=SR26410115859, DOI: https://dx.dx.doi.org/10.21275/SR26410115859