To cope with the weak grid stability issue of grid-tied Voltage Source Converters (VSCs), this letter proposes an Artificial Neural Network (ANN)-based approach for online stabilization control of the grid-tied VSC with the pole-tracking feature. First, an ANN is adopted to establish the mapping between the control parameters and the closed-loop poles of the grid-VSC system, serving as a computationally light model surrogate that is favorable for real-time control applications. Then, an online parameter search algorithm enabling simultaneous tuning of multiple controllers and parameters is developed, by which the systems poles under a new grid condition can be pulled to the reference ones, i.e., achieving the pole-tracking-based stabilization control of this work. Finally, the efficacy of the proposed method along with its stabilization effect is verified by MATLAB simulations and experimental results.
|Journal||IEEE Transactions on Industrial Electronics|
|Number of pages||8|
|Publication status||Published - 2022|
- Artificial neural network (ANN)
- Stabilization control
- Voltage source converter (VSC)