AI, machine learning to improve power distribution: Khattar
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Take your experience further with Premium access. Thought-provoking Opinions, Expert Analysis, In-depth Insights and other Member Only BenefitsArtificial Intelligence (AI) and machine learning (ML) will be central to building intelligent, consumer-centric and self-optimising electricity distribution networks, said Power Minister Manohar Lal Khattar on Sunday.
Addressing a two-day national conference on digital technologies in the power sector at Bharat Mandapam in Delhi, the minister said AI and ML applications such as smart meter analytics, digital twins, predictive maintenance, theft-detection systems, appliance-level insights, automated outage prediction and GenAI-based decision support can significantly improve consumer experience and operational efficiency.
He praised the strong participation from industry, states, innovators, academia and technology partners, and noted the variety of solutions presented by DISCOMs, AMISPs, technology providers and home-automation firms.
Calling for closer collaboration, the minister urged all DISCOMs to work with stakeholders to create smart, reliable and consumer-focused distribution systems. He said it was equally important to engage consumers and address misinformation around new technologies, adding that public support would be crucial for large-scale adoption.
He said the AI and ML-based solutions showcased at the conference demonstrated how technology can rebuild trust in the sector by helping households manage consumption better, preventing outages before they occur, protecting honest consumers from the burden of electricity theft, reducing losses and optimising power purchase costs.
Such digital tools, he said, could enable DISCOMs to reinvest in stronger infrastructure and contribute to India’s emergence as a leader in digital electricity reform.
Power Secretary Pankaj Agarwal said the ministry remained committed to expanding digital systems and supporting the deployment of AI and ML solutions that deliver measurable operational and financial gains.