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Technical Dialogue

Wind Energy Conversion Systems

D21.10 - LSTM-Based Sub-Synchronous Oscillation Detection Scheme for Type 4 Wind Farm Interfaced with Weak AC Grid

Thursday, March 20, 2025
11:30 AM – 1:30 PM ET
Location: Level One, Hall A3
Sub-synchronous oscillations (SSO) pose a significant threat to the stability of a power grid integrated with wind energy sources. Specifically in Type 4 wind farms operating under weak grid conditions. The adverse effects of this type of SSO include sustained oscillations in the active power, point of common coupling (PCC) voltage, and output current which can pose severe threat to the stability of the system and may lead to cascaded tripping across the network. Given these risks, it is crucial to ensure the effective and timely detection of SSO to mitigate potential instability and prevent potential cascading failures. Conventionally, SSO is identified by performing frequency scanning, developing and analyzing mathematical models and implementing impedance scanning approach for Type 3 wind turbine generators (WTG). This paper presents a lightweight intelligent machine learning-based approach for detecting SSO in the output of wind farms equipped with Type 4 WTGs. The proposed SSO detection scheme leverages double layer LSTM (DL-LSTM) based neural network to devise swift, effective, and accurate SSO detection, addressing the shortcomings of previous approaches.