Research on parameter identification of high-head hydropower MMC-HVDC system based on Sobol sensitivity analysis and adaptive cuckoo search algorithm

With the increasing complexity of high-head hydropower systems and the rapid development of flexible DC transmission technology, accurate electromagnetic transient (EMT) modeling of hydropower flexible DC systems is essential. To address the challenge of parameter acquisition, this manuscript proposes a method based on Sobol sensitivity analysis and an adaptive cuckoo search (ACS) algorithm for parameter identification. First, an EMT model is constructed, and Sobol sensitivity analysis is used to evaluate parameter influence. Key parameters with high sensitivity indices are selected for further optimization. Finally, the ACS algorithm identifies these parameters with high accuracy. The case study results show that ACS outperforms both standard cuckoo search and particle swarm optimization (PSO) algorithms in terms of convergence speed and identification accuracy. Simulation results confirm the validity of the identified parameters across various operating conditions, demonstrating the method’s effectiveness and generalizability.