Fault section estimation in electric power systems using an artificial immune system algorithm - Leão, Fábio Bertequini [UNESP] (2008)
This work proposes an unconstrained binary programming (UBP) model for fault section estimation in power systems. UBP model consists in a set of equations that represent in a logical way the expected states of the relays of the apparatus protection system. An artificial immune system algorithm (AISA) is developed in order to find the correct fault section estimate provided by the data from the supervisory control and data acquisition (SCADA) system. The proposed methodology is tested using part of the South-Brazilian electric power system. Control parameters of the AISA are calibrated to increase the efficiency and velocity of the algorithm. Results show the potential and the efficiency of the proposed methodology to fault section estimation online in electric power systems.