Performance of a new asset management model for power transformers based on monitoring systems

Abstract

When analyzing the performance of power transformers in distribution systems, it is important to identify the operating status of these devices, since they are a key factor for meeting the power demand requirements. For this reason, some methods are currently being developed to diagnose the transformer condition for maintenance forecasting and to corroborate the proper operation of the electrical system. However, these models are difficult to apply outside their scope of approach, due to their dependence on a significant amount of information to give a diagnosis. For this reason, this article presents a new management system for a fleet of transformers based on day-ahead prediction and a fuzzy logic classification module applied in a Smart Grids system. In this way, the applicability of this system was identified with different types of energy demand and a reduced number of data, thus showing different results from three models previously implemented.

Keywords

• asset management
• smart grids
• classification
• data forecast