AI-Optimized Smart Grids: Powering India's Renewable Energy Transition for a Sustainable Digital Economy

Abstract India's transition toward a renewable energy-led economy faces critical challenges in grid stability, demand forecasting, and efficient integration of intermittent power sources such as solar and wind. Artificial Intelligence (AI) is increasingly central to overcoming these constraints, enabling predictive load forecasting, real-time fault detection, and autonomous demand-response management across smart grid. Grid Mission, the IndiaAI Mission, and NITI Aayog's National Strategy for Artificial Intelligence. It further examines barriers to scale, including high implementation costs, inconsistent data interoperability across state utilities, cybersecurity vulnerabilities in AI-integrated grid systems, and the skills gap in AI-energy hybrid expertise. Through a review-based analytical framework, the paper proposes an integrated model aligning AI-enabled smart grid deployment with SDG-7 (Affordable and Clean Energy) and SDG-13 (Climate Action) within India's Viksit Bharat @2047 vision. The findings suggest that AI-optimized energy systems, if scaled with supportive policy and skilled workforce development, can position India as a global leader in sustainable, technology-driven energy infrastructure.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-30
DOI
https://doi.org/10.5281/zenodo.22722838
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-Optimized Smart Grids: Powering India's Renewable Energy Transition for a Sustainable Digital Economy

Kiruthika B, Kesna Prince, Nirmala M
Zenodo (CERN European Organization for Nuclear Research)
Smart Grid Security and Resilience
article

AI-Optimized Smart Grids: Powering India's Renewable Energy Transition for a Sustainable Digital Economy

Kiruthika B, Kesna Prince, Nirmala M
article en

Abstract

Abstract India's transition toward a renewable energy-led economy faces critical challenges in grid stability, demand forecasting, and efficient integration of intermittent power sources such as solar and wind. Artificial Intelligence (AI) is increasingly central to overcoming these constraints, enabling predictive load forecasting, real-time fault detection, and autonomous demand-response management across smart grid. Grid Mission, the IndiaAI Mission, and NITI Aayog's National Strategy for Artificial Intelligence. It further examines barriers to scale, including high implementation costs, inconsistent data interoperability across state utilities, cybersecurity vulnerabilities in AI-integrated grid systems, and the skills gap in AI-energy hybrid expertise. Through a review-based analytical framework, the paper proposes an integrated model aligning AI-enabled smart grid deployment with SDG-7 (Affordable and Clean Energy) and SDG-13 (Climate Action) within India's Viksit Bharat @2047 vision. The findings suggest that AI-optimized energy systems, if scaled with supportive policy and skilled workforce development, can position India as a global leader in sustainable, technology-driven energy infrastructure.

Zenodo (CERN European Organization for Nuclear Research)
Hindustan Institute of Technology and Science (IN)
Openalex Percentile: Top 14%
Smart Grid Security and Resilience
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AI-Optimized Smart Grids: Powering India's Renewable Energy Transition for a Sustainable Digital Economy — Kiruthika B, Kesna Prince, et al. · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS