Showing papers by "Matti Lehtonen published in 2000"

Comparison of artificial neural networks and conventional algorithms in ground fault distance computation

Abstract: This paper gives a comparison between an artificial neural network method and a differential equation algorithm and wavelet algorithm in transient based earth fault location in the 20 kV radial power distribution networks. The items discussed are earth fault transients. Signal pre-processing and the performance of the proposed distance estimation methods. The networks considered are either unearthed or resonant earthed. The comparison showed that the neural network algorithm was better than the conventional algorithms in the case of very low fault resistance. The mean error in fault location was about 1 km in the field tests using staged faults, which were recorded in real power systems. With higher fault resistances, the conventional algorithms worked better.

An advanced model for automatic fault management in distribution networks

Abstract: An automatic computer model, called the FI-model, for fault location, fault isolation and supply restoration is presented. The model works as an integrated part of substation SCADA and medium voltage distribution network automation systems, including protective relays and AM/FM/GIS. In the model, three different techniques are used for fault location: computed fault distance; analysis of fault indicator readings; and statistical analysis of the line section fault frequencies. Once the faulty section is identified, it is automatically isolated by the remote control of line switches, and supply is restored into the remaining parts of the feeder.