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Data-Mining-Based Intelligent Differential Relaying for Transmission Lines Including UPFC and Wind Farms

This paper presents a data-mining-based intelligent differential relaying scheme for transmission lines, including flexible ac transmission system device, such as unified power flow controller (UPFC) and wind farms. Initially, the current and voltage signals are processed through extended Kalman filter phasor measurement unit for phasor estimation, and 21 potential features are computed at both ends of the line. Once the features are extracted at both ends, the corresponding differential features are derived. These differential features are fed to a data-mining model known as decision tree (DT) to provide the final relaying decision. The proposed technique has been extensively tested for single-circuit transmission line, including UPFC and wind farms with in-feed, double-circuit line with UPFC on one line and wind farm as one of the substations with wide variations in operating parameters. The test results obtained from simulation as well as in real-time digital simulator testing indicate that the DT-based intelligent differential relaying scheme is highly reliable and accurate with a response time of 2.25 cycles from the fault inception.