A new arc-based model and condition monitoring algorithm for on-load tap-changers

An on-load tap-changer (OLTC) regulates the output voltage level of transformer by changing the winding voltage ratio without current interruption. It is one of the most expensive and vulnerable parts of power transformers. Therefore, modeling and condition monitoring (CM) of OLTCs are important for the power system operation. This paper presents a new modeling principle for OLTCs based on the circuit breaker (CB) arc models. There is a sequence of switching events with certain timings during each operation of OLTC. These switching operations are modeled individually and a full model of OLTC operation is derived. Computer simulation studies and the measurements captured from the real-time test studies of OLTC operation verify and validate the performance of the proposed OLTC model. On the other hand, the instantaneous differential power of tap-changing transformer measured from its input and output terminals is used to calculate the arcing power and energy associated with OLTC operation. The cumulative arcing energy is a good indication of the electrical wear of OLTC contacts. Therefore, it is used to propose a novel CM algorithm for OLTCs. The proposed method considers the effects of both arcing voltage and current signals to accurately estimate the arcing energy. The results obtained from computer simulation studies demonstrate that the proposed algorithm accurately evaluates the electrical wear of OLTC contacts and determines the inspection or maintenance schedules of OLTC contacts.