Renewable Energy Transition in India: Role of Artificial Intelligence in Optimising Renewable Energy Generation and Distribution
Sweety Supriya
Dr. Sweety Supriya, Assistant Professor, Department of Electronics, L. S. College, Muzaffarpur (Bihar), India.
Manuscript received on 18 April 2026 | First Revised Manuscript received on 01 May 2026 | Second Revised Manuscript received on 09 May 2026 | Manuscript Accepted on 15 May 2026 | Manuscript published on 30 May 2026 | PP: 1-8 | Volume-13 Issue-5, May 2026 | Retrieval Number: 100.1/ijies.D114813040426 | DOI: 10.35940/ijies.D1148.13050526
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: India is prioritising the deployment of renewable energy as a central pillar of its sustainable development policy and climate action plan. This shift towards renewable energy systems presents complex operational constraints arising from the intermittency of renewable energy sources, information asymmetries in forecasting power requirements, and the need for smart and robust energy infrastructure. In this context, this review paper aims to explore the evolving role and potential of Artificial Intelligence (AI) in facilitating sustainable energy transitions. Drawing on interdisciplinary literature, this paper explores the application of AI to data-driven decision-making to enhance renewable energy forecasting and intelligent energy storage management, thereby improving grid stability. Further, by drawing on theoretical and empirical insights, the paper seeks to contribute to the identification of key pathways, limitations, and policy-oriented considerations for shaping the future deployment of AI in sustainable energy production and distribution. The paper finds that recent developments in AI models and machine learning-based technologies, and their deployment in the renewable energy ecosystem, hold great potential for advancing renewable energy generation and distribution.
Keywords: Green Energy, Energy Storage System, Grid Balancing, Artificial Intelligence, Machine Learning, Forecasting Techniques.
Scope of the Article: Electrical Engineering