Integrating Large Language Models into Data-Driven Frameworks for Smart Meter Analytics

The evolution of metering technologies has enabled the collection of a vast amount of energy consumption data, offering new opportunities for more efficient energy management. While utility providers increasingly leverage machine learning and data visualization to simplify and optimize data analysis, current systems often present barriers in understanding collected data. This paper introduces a novel multi-agent architecture that integrates Large Language Models (LLMs) to enhance the interpretability of smart meter data. Developed within the Digital Enterprise initiative by Lutech S.p.A., the proposed framework enables natural language interactions and the generation of energy-related reports. An early evaluation has been conducted through a series of basic interaction tests, demonstrating the feasibility of the approach and its potential to improve data-driven decision-making.