A fuzzy inference-based approach for estimating power transformers risk index

Abstract

Risk assessment is a key point for power system operators interested in the implementation of asset management systems. Among critical electrical assets, the power transformer is probably the most representative. This paper presents a novel method for estimating a risk index for power transformers. The proposed method is based on three Fuzzy Inference Systems (FIS), aimed to integrate expert criteria for the creation of rules and the definition of the membership functions of the entries. The first FIS is dedicated to the calculation of a transformer Health Index (HI), based on the results of the physical-chemical tests normally performed on the insulating liquid of the units. The second FIS is oriented to the determination of a Consequence Factor (CF) of the final failure of the power transformer, and it is determined considering aspects such as overload to other assets, average load supplied by the unit, critical loads supplied, oil volume, proximity to other buildings and penalties for the unavailability of the asset. The last FIS combines the results of the previous FIS, i.e., HI and CF, to provide an estimation of the transformer risk index. The methodology has been designed to perform management of power transformer fleets by allowing decisions to be made, regarding investments, based on risk assessment. The proposal has been tested on a fleet of 15 units. Obtained results show that the FIS for combining HI and the CF leads to more consistent risk indexes, than those obtained when performing the conventional operation of multiplication between HI and FC.