Leveraging RAG for Reasoning and Analyses of Electricity Distribution Codes

Electricity distribution codes are dense, complex regulatory documents that govern the planning, operation, and management of power grids. Understanding and comparing these codes across different countries is crucial for enhancing grid resilience, integrating renewable energy sources, and facilitating more informed planning. However, their technical language and voluminous nature make manual analysis time-consuming and prone to oversight. There is a pressing need for automated, intelligent tools that can semantically interpret these codes, extract relevant insights, and support decision-makers in navigating regulatory complexity efficiently and accurately. This paper contributes by; (1) introducing a novel Retrieval-Augmented