AI/ML-Based Applications Set to Transform India’s Power Sector

AI/ML-Based Applications Set to Transform India’s Power Sector

Artificial Intelligence (AI) and Machine Learning (ML) based applications will play a pivotal role in transforming India’s power distribution systems into intelligent, consumer-centric, and self-optimising networks, Hon’ble Union Minister of Power Shri Manohar Lal said at the Two-day National Conference on the Use of AI/ML Technologies in Power Distribution held at Bharat Mandapam, New Delhi.

Addressing delegates at the event, the Hon’ble Union Minister highlighted how advanced AI/ML solutions—such as smart meter analytics, digital twins, predictive maintenance, theft detection, appliance-level consumer insights, automated outage prediction and Generative AI-based decision support systems—can enhance both consumer experience and operational efficiency across the power distribution sector.

Shri Manohar Lal noted that these technologies will empower households to better manage electricity consumption, prevent outages before they occur and protect honest consumers from the financial burden of power theft, while also enabling Distribution Companies (DISCOMs) to reduce losses, optimise power purchase costs and reinvest in grid infrastructure, thereby positioning India as a global leader in digital electricity reform and future-ready grid governance.

In his remarks, the Hon’ble Union Minister also called for active collaboration with industry stakeholders, technology partners and consumers to accelerate the adoption of AI/ML-driven innovations and remove misinformation that could impede technology acceptance.

The event was attended by senior officials from the Ministry of Power, including Shri Pankaj Agarwal, Secretary, along with representatives from DISCOMs, Advanced Metering Infrastructure Service Providers, Technology Solution Providers and academia. Participants showcased cutting-edge use cases demonstrating how AI/ML can drive smart, efficient and sustainable power distribution nationwide.

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