Optimizing Transformer Management: GIS Analysis and ESRI Tools Field Deployment
Presentation Time: Fri, 12/06/2024 - 14:30
Keywords: transformer management, GIS analysis, supply chain optimization, asset management, utility operations
The COVID-19 pandemic disrupted supply chains, causing transformer costs to rise two to five times compared to the 2019 cost, and extending lead times from a few months to over 18 months. To address this, the Navajo Tribal Utility Authority (NTUA) aimed to locate idle transformers, referred to as "hanging inventory," for reuse. However, NTUA lacked an efficient system for tracking these transformers and relied on employee reports from field visits. To improve this process, I developed a Python-based GIS analysis using existing transformer, powerline, and meter point data to map the relationships between transformers and downline meters. By cross-referencing active meters, I identified over 2,000 potential idle transformers. We also deployed over 100 tablets equipped with ESRI field software to assist field workers in accurately capturing and updating transformer locations. The project enabled significant data cleanup, uncovering mislocated meters and errors in the transition to automated metering infrastructure systems. These findings have enhanced NTUA's asset management by identifying unused transformers, improving resource allocation, and streamlining future maintenance efforts. As a result, NTUA can now more effectively manage transformers, helping mitigate ongoing supply chain challenges.
