Adaptive Power Quality Estimation for Smart Grid Applications using Secant Cost Based Fractional Algorithm

Tracking and mitigation of power quality (PQ) disturbances are two most challenging tasks during integration of smart grid with the conventional power networks. Estimation models using adaptive filtering algorithms are quite effective to track the time varying and short duration PQ disturbances. An efficient estimation model for time-varying disturbances is proposed using fractional adaptive filtering with secant cost function and tested using standard real time database with detail comparison results.