Optimal estimation of harmonics in a dynamic environment using an adaptive bacterial swarming algorithm

This study is concerned with optimal estimation of power system harmonics in dynamic environment, in which the fundamental frequency deviates with time. The estimation process utilises an adaptive bacterial swarming algorithm (ABSA), which is adaptive to dynamic environment, to estimate the frequencies and phases of the fundamental frequency, integral harmonics and inter-harmonics, along with a least-square method to estimate the amplitudes. ABSA is a generic optimisation algorithm designed from an adaptive searching framework that combines the underlying mechanisms of bacterial chemotaxis, quorum sensing and environment adaptation. Simulation studies have been carried out in three different conditions in comparison with generic algorithm (GA), and the results have shown that ABSA can effectively solve this type of problem and outperforms GA remarkably.