Evaluating the Improvement of Partial Discharge Localization Accuracy Using Frequency Response Assurance Criterion

Subject Areas : International Journal of Smart Electrical Engineering

Amir Mohammadirad ¹ , Ramin Vakili ² , A.A. Shayegani Akmal ³

1 - School of Electrical and Computer Engineering, University of Tehran ,Tehran, Iran
2 - School of Electrical and Computer Engineering, University of Tehran ,Tehran, Iran
3 - School of Electrical and Computer Engineering, University of Tehran ,Tehran, Iran

Received: 2018-07-05 Accepted : 2018-08-23 Published : 2018-09-01

Keywords: PD, Partial discharge, Correlation method, Transformer winding, FRAC, PD location,

Abstract :

Partial Discharge (PD) is the most important source of insulation degradation in power transformers. In order to prevent catastrophic failures in transformers, PDs need to be located as soon as possible so that maintenance measures can be taken in time. Due to the structural complexity of windings, locating the PD source inside a transformer winding is not a simple task. In this paper, the efficacy of the proposed Frequency Response Assurance Criterion (FRAC) correlation technique for finding the location of a PD source in a transformer winding is evaluated and compared with two well-known correlation techniques in this regard, that are Time domain correlation and Kullback- Leibler divergence. The responses of the winding to PD pulses, generated by Heidler function, of known pulse duration applied in parallel along the whole sections of the winding are considered as the reference data. In addition, the captured responses of the winding generated by injecting the PD pulses of arbitrary shapes and magnitude along the various sections of the winding are taken as the test data. Subsequently, the location of the PD source is determined by finding the maximum FRAC value between the reference signals and the test signal. First, a simulation case-study is carried out to show how the proposed method can be applied to locate a PD source. Subsequently, the results of the proposed method are compared with the time-domain and Kullback–Leibler divergence correlation techniques. Finally, the proposed method is validated with the experimental results. The simulation and experimental results demonstrate that the proposed method is more effective in precisely determining the location of a PD source even in a very noisy condition.