Localization of Sub/super-synchronous Oscillation Sources in Wind Power Systems Based on Deep Adaptation Network
Qi Hao, Jin‐Yuan Wang, Xinyan Wang, Jufeng Li, Chenbo Su, Chongru Liu · 2023
When persistent sub/super-synchronous oscillations occur in a wind power system, timely and accurate localization of the wind turbine that causes the oscillations is the first and foremost task to suppress the oscillations precisely. However, the scarcity of actual system oscillation data causes a serious data bottleneck in the research of localization based on data-driven technology. Based on this, this paper proposes an online localization method of oscillation source based on deep adaptation network. Through the transfer and generalization between data, the problem of scarcity and difficulty in obtaining the oscillation data of the actual system is solved. The analysis of examples shows that the oscillation source localization method proposed in this paper has better performance in terms of model training speed as well as localization accuracy.