Harmonic Source Classification based on GRU Network

Tongdan Xue

Abstract: With the development of ultra-high voltage and smart grids, the issue of power grid harmonic pollution caused by nonlinear loads and equipment has become more prominent. Harmonic pollution leads to increased energy consumption and poses safety risks to the operation of the grid, resulting in significant economic losses. In the comprehensive management of grid harmonics, the classification of harmonic sources is an urgent issue that needs to be addressed. In this context, this paper proposes a harmonic source classification method based on the GRU network. This method utilizes the GRU model, which is capable of long-term memory, to extract inherent features from harmonic data for classification, achieving good classification results. It provides a necessary foundation for the effective implementation of harmonic analysis and management.

Keywords: smart grid, GRU, harmonic suppression