Abstract
In order to effectively detect the waveform characteristics of the closing inrush current of distribution transformers and distinguish between the magnetizing inrush current and the fault current when closing, this paper proposes a new method based on neighborhood preserving embedding (NPE) and principal component analysis (PCA) transformer closing inrush current detection method. This method can detect and process the global and local feature information of the data. First, the NPE-PCA algorithm is used to reduce the current data to two-dimensional space, and then the fitting error σ is obtained by fitting the two-dimensional space data. The relationship between σ and a given threshold is used to identify the magnetizing inrush current when closing. Finally, a model is built on the ATP/EMTP platform to test the proposed method for detecting the waveform characteristics of the closing inrush current. The simulation results show that the NPE-PCA inrush current waveform detection algorithm proposed in this paper can effectively identify the waveform characteristics of the transformer closing inrush current, which is consistent with the second harmonic wave. Algorithm comparison analysis shows that the performance of this algorithm is better.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.