Power Minister launches CEA’s Stellar tool
Author: PPD Team Date: December 9, 2025
The Minister of Power Shri Manohar Lal launched the Strategic Expansion for Long Term Load Adequacy and Resilience tool developed by the Central Electricity Authority. He said that Artificial Intelligence and Machine Learning will be central to building consumer-focused, self-optimising and reliable distribution networks. He was speaking at the two-day National Conference on AI and ML in the power distribution sector at Bharat Mandapam in New Delhi.
He said that AI and ML can strengthen smart meter analytics, digital twins, predictive maintenance, theft detection, appliance-level insights, outage prediction and decision support. He noted the participation of distribution companies, Advanced Metering Infrastructure Service Providers, Technology Solution Providers and Home Automation Solution Providers. He asked distribution companies to work with industry, states and technology partners and to build public confidence in new technologies.
He said that AI and ML can help households manage demand, reduce outages and protect honest consumers from theft-related losses. He said that data driven tools can lower losses, optimise power purchase and support long term network investment. He said these advances position India to strengthen digital electricity governance.
The Secretary of the Ministry of Power Shri Pankaj Agarwal said the Ministry is committed to digitalisation across distribution companies and to scaling AI and ML solutions that deliver measurable benefits. He emphasised the need for capacity building, secure data frameworks and interoperability.
The conference received 195 applications under a national call for innovation. After screening, 51 solutions were evaluated on 06 December 2025. The winners were TNPDCL and MP East in the distribution company category, Tata Power and Apraava in the Advanced Metering Infrastructure Service Provider category, Pravah and Flock Energy in the solution provider category and Tata Power in the home automation category.
Image Source: PIB
