Co-authored by Ruchika Chawla, Associate Partner, 乐鱼(Leyu)体育官网 in India.
Power distribution is a critical link in the electricity value chain, interfacing with the end-customers and the only revenue source for the entire value chain. As distribution utilities continue to provide reliable and affordable electricity to all, they need to address both traditional grid challenges such as grid reliability, quality of supply, access, affordability, increasing and evolving demand, aging infrastructure, and high electricity transmission and distribution losses along with emerging challenges of renewable energy integration, urbanization, resilience, cybersecurity and data management.
Gen AI can be instrumental in building solutions for power distribution for addressing both traditional and emerging challenges. Classical AI has already been playing a key role in forecasting, schedule optimization, integration of renewables, grid stabilization/ resilience, revenue assessment, anomaly detection, consumer-centric services, etc. Gen AI is an important complement that boosts capabilities of utilities to bring significant improvements in efficiency and efficacy, and also 鈥渢urbocharge鈥� the power of classical AI and other digital facilities.
In India, use of classical AI has been limited, but is picking up. Indian utilities are already a data powerhouse鈥攇enerating data around energy consumption, financial transactions, customer-initiated interactions (complaint, feedback, etc.). Furthermore, with the roll-out of 250 million smart meters, the data volume generated would be impossible to manage through rule-based analytics.1
Owing to its superior knowledge management capabilities (because of new age Large/Small/Tiny Language Models and their 鈥渃onversational鈥� abilities), Gen AI can be brought to bear on many areas of distribution utility operation. Broadly, the use cases will span across four areas 鈥� load forecasting and planning; grid and assets; revenue and customer; and governance and compliance (Refer graphic).