AI-Driven Distributed Renewable Energy: Powering India’s Citizen-Centric Energy Transition

Why in News ?

At the India AI Impact Summit held at Bharat Mandapam, policymakers and global experts deliberated on the theme ‘Global Mission on AI for Energy Scaling through Citizen-Centric India Energy Stack’.The government highlighted Artificial Intelligence (AI) as a transformative force for scaling Distributed Renewable Energy (DRE) and modernising India’s power sector.

Background and Context

India is undergoing a dual transformation:

• Energy Transition (towards renewables),
• Digital Transformation (AI and Digital Public Infrastructure).

With rising rooftop solar, solar pumps, and decentralised energy systems, traditional grids face structural stress. AI integration is now viewed as critical to managing this complexity and enabling predictive governance.

Understanding Distributed Renewable Energy (DRE)

DRE refers to decentralised, small-scale renewable systems (kW to MW scale) located near consumption points.

Examples include:

• Rooftop solar installations
• Small wind turbines
• Biomass units
• Solar irrigation pumps

Unlike centralised power plants, DRE promotes:

• Local generation
• Reduced transmission losses
• Consumer participation (rise of “prosumers”)

India’s Renewable Energy Landscape

Key Data:

• 52% (≈272 GW) of total installed capacity from non-fossil sources.
  • Solar capacity: ~140 GW.
  • DRE capacity: 38 GW.
• Nearly 18 GW added in DRE segment in last 15 months.

Major Schemes:

• Pradhan Mantri Surya Ghar Muft Bijli Yojana
• Pradhan Mantri KUSUM Yojana

Public investment:

• ~$9 billion for rooftop solarisation
• ~$4 billion for PM-KUSUM

Why AI is Crucial for the Next Phase ?

Structural Challenges:

• Transformers designed for one-way power flow.
• Emergence of prosumers feeding power into grids.
• Stress on distribution networks.
• Need for real-time balancing and predictive maintenance.

AI Applications in DRE:

• Weather forecasting for solar prediction
• Asset performance monitoring
• Predictive load management
• Peer benchmarking
• Grid stability optimisation
• B2B electricity trading enablement

Government vision: Shift from reactive governance to predictive governance.

AI as Development Infrastructure

AI is being conceptualised as core infrastructure—similar to:

• Power grids
• DISCOM networks
• Smart meters

This aligns with India’s Digital Public Infrastructure (DPI) model. The proposed India Energy Stack aims to replicate the success of the India Stack in fintech.

Strategic Vision:

• Scale AI beyond pilot projects
• Develop interoperable digital architecture
• Position India as a global AI-energy solutions leader

Governance and Regulatory Dimensions

Energy transition increases system complexity. AI integration raises concerns about:

• Data sovereignty
• Cybersecurity
• Big Tech monopolisation
• Algorithmic concentration

Governance Principles Proposed:

• Open standards (similar to TCP/IP model)
• Open-source AI systems
• Anti-monopoly safeguards
• Promotion of domestic innovation (Atmanirbhar Bharat)

What Success May Look Like (Next 2–3 Years)

• Reduction in consumer power costs
• Enhanced industrial competitiveness
• Transition from consumer to prosumer empowerment
• Grid readiness for high renewable penetration
• Improved energy access and reliability

Key Challenges 

1. Legacy Grid Infrastructure

Transformers and feeders require modernisation.

2. DISCOM Financial Stress

AI deployment requires financial viability of utilities.

3. Data Governance Risks

AI systems require robust regulatory oversight.

4. Digital Divide

Unequal access to smart infrastructure may widen disparities.

Way Forward

• Build interoperable India Energy Stack
• Invest in AI-driven grid modernisation
• Strengthen data privacy and cybersecurity frameworks
• Encourage startup ecosystem participation
• Align AI integration with India’s Net Zero 2070 and NDC commitments

Significance

AI-powered DRE convergence is not merely technological—it is strategic.

It determines whether India:

• Becomes a passive technology importer, or
• Emerges as a global architect of citizen-centric, decentralised energy systems.

The AI–Energy nexus sits at the heart of:

• Climate action
• Economic competitiveness
• Energy security
• Digital sovereignty