Asset Management Model for the Transformer Fleet of the National Laboratory of Smart Grids (LAB+i) Based on Fuzzy Logic and Forecasting

Abstract

Smart grids have gained attention in recent years in the field of smart cities as a key parameter for the electrical power service, adapted to the new forms of generation and processes associated with the use of electricity. In this sense, the diagnosis of the state of the infrastructure is important to ensure its operation, in which the power transformer is the key element. For this reason, this article presents an Asset Management methodology based on prediction and fuzzy logic to identify the condition of the transformer fleet from the National Laboratory of Smart Grids (LAB+i), considering its conditions. First, the forecasting system is presented together with the base parameters of the fuzzy logic system. Then an implementation analysis is performed with real data. This development allowed identifying the opportunity of using this system in different scenarios, with the challenges and benefits of the prediction methods in the Asset Management framework.