New Algorithm To Identify Inrush Currrent Based On Improved EMD

Power transformers are one kind of most important power equipments in power systems. Its safe operation plays a directly important role in whether transformer substation and power system operates safely or not. At present,the main protection of the power transformer is the differential protection. A new algorithm based on Empirical mode decomposition (EMD) is presented for solving the mal-operation problem in transformer main protection due to magnetizing inrush current.Empirical mode decomposition (EMD), which is the core mechanic of the Hilbert-Huang transform(HHT), is a local, fully data driven and self-adaptive analysis approach. It is a powerful tool for analyzing multi-component signals. Aiming at the reduction of scale mixing and artificial frequency components, an improved scheme was proposed for analysis and reconstruction of nonstationary and multicomponent signals. The improved EMD method uses the wavelet analysis method and normalized correlation coefficient to deal with the problems. Because the inrush current is a peaked wave with nonstationary component, a new algorithm based on improved EMD is presented for fast discrimination between inrush current and fault current in power transformers. Theoretical analysis and dynamic simulation results show that the method is effective and reliable under various fault conditions and simple to be applied.