India is evaluating a proposal to introduce an AI-driven Solar Inverter Fault Prediction System in 2026 to help reduce sudden breakdowns and improve rooftop solar reliability. Sources told SolSetu that MNRE, along with several inverter manufacturers, is reviewing early-stage models capable of predicting inverter failures days or weeks before they occur.

This would be India’s first national predictive maintenance platform aimed at home rooftop solar customers.

Why AI-Based Fault Prediction Is Important

More than 60% of rooftop service complaints nationwide are related to:

• Inverter shutdowns
• DC over-voltage faults
• Loose wiring or MC4 connector heating
• Firmware errors
• Earthing and SPD-related failures

Industry analysts estimate that predictive alerts could reduce inverter downtime by up to 40% annually.

How the Fault Prediction System May Work

The proposed system may use:

• Real-time inverter analytics from Wi-Fi/GPRS data
• AI models trained on past fault patterns
• Temperature, voltage, and load fluctuation monitoring
• DISCOM grid health data
• Predictive scoring to estimate risk of failure

Consumers may receive alerts via SMS, official portals, or inverter apps.

Expected Benefits for Consumers

If implemented, homeowners may get:

• Early warnings before inverter failure
• Lower repair costs
• Higher overall solar generation
• Reduced system downtime
• Faster technician response

Installers can also use prediction data to schedule preventive maintenance more efficiently.

Pilot States Likely in Phase 1

Based on early discussions, pilot tests may begin in:

• Maharashtra
• Gujarat
• Tamil Nadu
• Karnataka
• Delhi

The national rollout could follow in late 2026 depending on pilot performance.

SolSetu will continue to track this development and provide updates as MNRE finalizes the framework.