Optimal Evaluation of Power System Harmonics in Smart Grid Based on Grey Wolf Optimizer

The modernization of traditional grid towards a smart gird is being accomplished for the improvement of system reliability, to facilitate the renewables integration with the amelioration of energy consumption and power quality management system. Recently, Power quality has acquired enormous attention due to wide usage of nonlinear loads, power electronics devices, renewable integration and sensitive operations in smart grid. Timely and accurate detection of power system harmonics are the key factors for an effective power quality protection strategy. In this paper, a new hybrid optimization framework based upon grey wolf optimizer and least square method (GWO-LS) is presented for the harmonic’s estimation in dynamic and noisy power signals. GWO-LS has a unique feature i.e. leadership behavior of grey wolves which differentiate it from other harmonic estimators. The proposed solution is tested for a standard test system and the simulation results prove that GWO-LS outperform the literature techniques in terms of percentage error, complexity level and computation time.