Abstract
This paper presents an intelligent fault location technique for the radial unbalanced distribution systems, based on the meseurments of Short Circuit Power (S/C.P) values at the primary bus. A Multi-Layer Feed ForwardNeural Network (ML-FFNN) with the tunned parameters is designed to evaluate the measurments. The estimated locations of different fault types are compared with the actual distances and Difference Percentage is calculated for each location. To examine the performance of the proposed technique in presence of DG units, the senario is also repeated including a DG unit in the simulated distribution network and the acuired result are presented. The proposed fault location technique is capable of being implemented with the small scale dataset which is applicable for the real distribution networks.
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