Hybrid HVDC system parameters tuning based on Robust Multi-Objective Optimization via Evolutionary Algorithms

The hybrid HVDC transmission system combines the advantages of the line commutated convertor (LCC) and the voltage source converter (VSC) which has great development prospect. Given the uncertainty and complexity in parameters tuning of control modules, this paper introduces a novel robust Multi-Objective Optimization via Evolutionary Algorithms (RMOEA). By searching pareto optimal solutions and robust solutions separately, each region's convergency and diversity performance under perturbance are enhanced appreciably. The improved RMOEA is used to optimize the PI parameters in the rectifier side controller and the inverter side dq axis decoupled dual-loop controller simultaneously. The simulation is implemented jointly by MATLAB and PSCAD software and the experiments results show that compared with the other optimization algorithm, the proposed RMOEA verifies the effectivity of improvements on robustness under the disturbances and tracking ability of preference.