Adaptive Multi-Parameter-Tuning for Online Stabilization Control of Grid-Tied VSC: An Artificial Neural Network-Based Method
Chen Zhang, Mohammad Mehdi Mardani, Tomislav Dragičević
Abstract
Voltage Source Converter (VSC) for grid integration of renewable energies are prone to have small-signal stability issues when connected to weak AC grids. Such stability issues largely arise from the lack of VSC control adaptivity to the varying grid condition (e.g., grid impedance). To address this issue, this letter presents an adaptive multi-parameter tuning method using the Artificial Neural Network. Innovative aspect of the proposal lies in that it enables the VSC to simultaneously tune multiple controller parameters online, which brings about a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">pole-tracking</i> -based stabilization control feature for the VSC. Experimental results demonstrate that the proposed method can effectively and adaptively stabilize the VSC when the grid impedance is varied.