Spatiotemporal Equivalent Modeling Method for Renewable Energy Clusters Containing Different Generator Models

[Objective] To improve the computational efficiency of dynamic analysis for large-scale renewable energy clusters， this paper investigates a typical renewable energy cluster connected to a 500 kV collection substation， and further studies cross-station and cross-type aggregation methods based on the existing single-machine equivalence of each station by unit type. [Methods] To address the errors caused by insufficient representation of spatiotemporal dynamic differences among heterogeneous equivalent units during further aggregation， an error-driven spatiotemporal aggregation equivalent modeling method for renewable energy clusters is proposed. In the temporal dimension， dynamic response differences among equivalent units are characterized to correct cross-station and cross-type dynamic behaviors. In the spatial dimension， the influence of the collector network is considered to calculate the equivalent impedance. Simultaneously， an error-threshold-driven mechanism adaptively updates model parameters according to operating conditions to balance accuracy and computational efficiency. [Results] Under different operating conditions and disturbance scenarios， the proposed method effectively captures the voltage dynamic response characteristics of the renewable energy cluster， and its adaptive parameter update capability is verified through threshold comparison and output fluctuation analysis. [Conclusions] The proposed method can effectively represent the spatiotemporal dynamic differences among cross-station and cross-type equivalent units. It reduces model complexity and improves computational efficiency while maintaining equivalence accuracy， providing an effective approach for dynamic analysis and equivalent modeling of large-scale renewable energy clusters.