Control Parameter Analysis of AC/DC Systems Based on Input to State Stability Theory and Regression Decision Tree

With the inevitable trend of renewable energy generation and DC transmission in modern power systems, the risk of AC and DC faults leading to high-power shocks and thus large-scale chain off-grid of new energy units, or even leading to system collapse, is increasing. Currently, there is room for further improvement in the control performance of traditional control methods due to issues such as control cost and control complexity. Meanwhile, the current power system security and stability analysis methods are difficult to support the quantitative assessment of the power grid stability level under a high proportion of new energy scenarios. Therefore, in this paper, based on the consideration of the interpretability of the algorithm, a control parameter analysis method for AC/DC systems based on Input to State Stability Theory and Regression Decision Tree is proposed, and simulations are carried out in a simplified system to authenticate the efficacy of the introduced method.