A Generative AI Framework for Intelligent Utility Billing CO 2 Analytics and Sustainable Resource Optimisation
For utility companies, it offers a unified approach to billing transparency, carbon tracking, and grid optimization, but the contribution is incremental as it combines existing methods without demonstrated performance gains.
The paper proposes an end-to-end framework integrating a generative-AI agent for natural-language billing, a transformer-based forecaster for day-ahead consumption, and modules for carbon analytics and load scheduling. No concrete results or numbers are provided.
Distribution utilities are now expected to deliver bills that customers can actually read attach a defensible carbon number to every kWh sold and schedule load against grid stress and emissions constraints We propose an end-to-end framework that unifies four production-grade capabilities under one architectural roof a generative-AI agent that drafts each customers natural-language billing statement from structured numeric inputs under a constrained decoding policy a transformer-based forecaster that supplies the day-ahead consumption estimate with calibrated quantile bands