Paired bacteria optimizer for power system fault signal identification

The accurate detection and location of a fault is crucial for power systems applications such as protective relaying and phasor measurement. As fault signals have unique mathematical expressions, this paper proposes a computational intelligence based method to estimate the parameters of the fault signal towards the minimum difference between the input signal and the reconstructed one. The optimization algorithm employed is paired bacteria optimizer (PBO), which is fast, accurate and stable. Hence, it is most applicable to solving such problems, as fault detection/location and fault signal identification require fast and accurate estimation of the signal's parameters. The performance of PBO has been demonstrated in this paper, and simulation studies have shown the superiority of the proposed method over traditional algorithms.