Data-Driven Regression-Based Transient Equivalent Modeling of Transmission Networks with High Renewable Energy Penetration
Conventional Thévenin equivalent models fail to capture the nonlinear low-voltage ride-through (LVRT) and current-limiting behavior of inverter-interfaced renewable generators, leading to significant errors in short-circuit current calculations near transmission-distribution boundaries. This paper proposes a transient equivalent model and parameter estimation method for transmission networks with high renewable penetration under specific operating conditions. The model augments the traditional ideal voltage source and equivalent impedance with a voltage-controlled current source (VCCS) and an additional short-circuit impedance. The VCCS control function aggregates all renewable generators, distinguishing between units that enter LVRT and those that do not. A data-driven regression approach estimates equivalent parameters using the additional short-circuit impedance as input. Validation on a modified IEEE 39-bus system with high renewable penetration confirms the model's rationality and the accuracy of the parameter estimation. The proposed model achieves superior short-circuit current calculation accuracy compared to the conventional Thévenin model, particularly for faults near the transmission-distribution interface where renewable generators experience voltage dips below 0.9 p.u. and exhibit non-smooth current response characteristics.