Barcelona 12-15 May 2003 Mansooreh Zangiabadi Iran Session 3 – Block 3.4 – Presentation & Kerman Regional Electric Company Fault Location in Distribution.

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Barcelona May 2003 Mansooreh Zangiabadi Iran Session 3 – Block 3.4 – Presentation & Kerman Regional Electric Company Fault Location in Distribution Systems based on Artificial Neural Networks and Application of GIS M.Zangiabadi M.R.Haghifam A.Khanbanha University of Tehran Tarbiat Modares University Kerman Regional Electric Co.

Mansooreh Zangiabadi Iran Session 3 – Block 3.4 – Presentation Barcelona May 2003 & Kerman Regional Electric Company Fault Location Estimation Off-Line Methods Trial and error method with energization the line section by section On-Line Methods High frequency transient signals Wavelets Pattern recognition Neural network

Mansooreh Zangiabadi Iran Session 3 – Block 3.4 – Presentation Barcelona May 2003 & Kerman Regional Electric Company Case Study Input data for neural network Voltage Current Simulation software EMTDC MATLAB Line model Bergeron model configuration of feeder and simulator output

Mansooreh Zangiabadi Iran Session 3 – Block 3.4 – Presentation Barcelona May 2003 & Kerman Regional Electric Company Simulator Output Single-phase to ground fault in the middle of feeder Three-phase to ground fault in the middle of feeder

Mansooreh Zangiabadi Iran Session 3 – Block 3.4 – Presentation Barcelona May 2003 & Kerman Regional Electric Company The Proposed Neural Network Structure Three-layer feed forward neural network Error back propagation training method Input data – voltage and current – are normalized Output layer Distance Flag which refers to lateral number

Mansooreh Zangiabadi Iran Session 3 – Block 3.4 – Presentation Barcelona May 2003 & Kerman Regional Electric Company The results of L-G fault Training data is prepared in pitches of 50 meters The resistance of fault is changed in steps of 5 from 0 to 25 ohms Fault Location (m) Fault Resistance (Ω) Error of ANN predicted location (m) Lateral Number

Mansooreh Zangiabadi Iran Session 3 – Block 3.4 – Presentation Barcelona May 2003 & Kerman Regional Electric Company Selecting the best structure Number of epochs is considered 1000 epochs Mean Square Error criterion evaluates the structure Error Percentage of Neural Network for L-G fault

Mansooreh Zangiabadi Iran Session 3 – Block 3.4 – Presentation Barcelona May 2003 & Kerman Regional Electric Company Structure of Neural Networks as Fault Locator Distance

Mansooreh Zangiabadi Iran Session 3 – Block 3.4 – Presentation Barcelona May 2003 & Kerman Regional Electric Company Combination with GIS Software

Mansooreh Zangiabadi Iran Session 3 – Block 3.4 – Presentation Barcelona May 2003 & Kerman Regional Electric Company Thanks for your attention I would also like to thank University of Tehran (UT) and Kerman Regional Electric Company (KREC) for their supports