Analysis of HVDC Transmission Lines Under Fault Surges Using Wavelet and Fuzzy Analysis

Traveling wave analysis process over the long High Voltages Direct Current (HVDC) transmission lines for internal and external fault surges is rarely tackled and still as a competitive research issue. Transient surges resulting from different internal and external faults may cause sever risk failure to the long HVDC lines. Once, a fault occurs over the HVDC transmission line, high frequency traveling waves (TW) are generated. These traveling waves propagate away from the fault position in both direction of the transmission line with approximately the light speed. During internal faults the traveling waves can be detected at both line terminals. For external faults, the traveling wave can be detected only at one-line terminal with zero at the other terminal. Therefore, the identification method for internal and external fault surges for HVDC lines can be proposed by comparing the amplitude of the traveling waves at both ends of line. In the current paper, analysis has been investigated to develop a technique for the fault surges discrimination over long HVDC transmission line with length up to 1000 km. The proposed technique is based on the travelling wave theory and the wavelet transformation integrated with artificial neuro-fuzzy interface (ANFIS) prediction system. The developed technique can precisely predict the exact fault surge voltage. Different simulation models are developed based on EMTP/MATLAB. the proposed technique can accurately discriminate between internal fault and external ones under various conditions. The results of the proposed technique exhibit a great convergence with the work in literature for transient surges discrimination.