Development of Current Harmonic Estimation Method by Extreme Learning Machine

초록

Due to the increasing of nonlinear loads such as converters and inverters connected to the electric power distribution system, and extensive application of harmonic generation sources with power electronic devices, disturbance of the electric power system and its influences on industries have been continuously increasing. Thus, it is difficult to construct accurate load model for active and reactive power in environments with harmonics. In this research, we develop current harmonics estimation method based on Extreme Learning Machine (ELM) with fast learning procedure for residential loads. Using data sets acquired from various residential loads, the proposed method has been intensively tested. As the experimental results, we confirm that the proposed method makes it possible to effective estimate current harmonics for various input voltage.

제목
Development of Current Harmonic Estimation Method by Extreme Learning Machine
저자
지평식; 이대종; 이종필; 김형철; 임재윤
발행일
2012-06-12
학회명
Proceedings of PMAPS 2012