Instability Mode Recognition of Grid- Tied Voltage Source Converters with Nonstationary Signal Analysis

With the increasing penetration of voltage-source-converter (VSC) -interfaced distributed generations (DGs) in power systems, oscillation issues have been widely concerned whereas the root cause and nature of the oscillation is sometimes not clear in real cases. This paper focuses on the instability mode recognition (IMR) based on a complete data-driven approach applied to the oscillation waves which can be obtained from the on-site recordings. To this end, we explore the Hilbert-Huang Transform (HHT) for diagnosing the root cause of instability, using only raw data such as the current and voltage waveforms which are accessible by operators. Special attention is paid to distinguish between the sub-synchronous oscillation (SSO) and the loss of synchronization (LOS) as they are two primary instability forms of grid-tied VSC which manifest with very similar waveforms. The pros and cons of the considered signal analysis tools in SSO and LOS recognition are discussed and new lines of investigations are proposed. The analysis and results presented in this paper could shed light on future data-driven analysis, e.g., serving as model-free or hybrid model database for artificial intelligence-based stability diagnosis and recognition.