A Generative AI Framework for Intelligent Utility Billing CO 2 Analytics and Sustainable Resource Optimisation

TL;DR

This paper presents an integrated generative AI framework for utility billing that includes natural-language bill drafting, load forecasting, and emissions analysis to promote sustainable resource management.

Contribution

It introduces a novel end-to-end architecture combining generative AI, transformer-based forecasting, and emissions analytics for utility billing and sustainability.

Findings

Generated bills are more readable and informative.

Forecasting model provides accurate day-ahead consumption estimates.

Framework supports sustainable resource optimization.

Abstract

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