Advanced Asset Management through Data Analytics: Upgrading Service Transformers to Boost Energy Efficiency in a Brazilian Distribution Utility

Abstract

This paper leverages data analytics to implement proactive strategies for upgrading service transformers in environments where data is scarce. The objective is to enhance energy efficiency, thereby supporting grid decarbonization while securing the economic health of utilities. The proposed approach involves three main steps: (i) assessing the loading and life expectancy of transformers, (ii) evaluating energy efficiency in various scenarios, and (iii) conducting financial analysis for implementing upgrading strategies. By using a dataset from a major Brazilian utility, comprising approximately 200,000 transformers, the study identifies a significant portion —over 70%— of underloaded units. Through a strategic selection process that includes relocating and replacing specific units, the data-driven approach not only improves operational efficiency but also substantially increases profitability. Additionally, sensitivity studies on key parameters reveal that upgrading service transformers with high-efficiency units (mineral oil transformers) results in favorable financial gains for the utility, with greenhouse gas reductions comparable to those achieved with green units (vegetable oil transformers), all within the 25-year regulatory lifetime.

Keywords: Asset Management, Distribution Systems, Electric Losses, Energy Efficiency, Financial Analysis, Service Transformers