Layered Parameter Optimization of MMC-HVDC PI Controller Based on Improved MOPSO

For MMC-HVDC(modular multilevel converter-high voltage direct current, MMC-HVDC) controller optimization, such problems as multiple control objectives, the relative influence among multiple PI controllers and the difficulty of PI parameter optimization are obvious. In this paper, layered parameter optimization of MMC-HVDC PI controller is proposed based on improved MOPSO method. In order to increase the diversity of the particles to avoid the population sinking into the local optimal solution, a mutation operation is introduced to the particles in the external memory. In order to improve the convergence of the algorithm and obtain a good Pareto frontier, a leading particle selection method is proposed based on membership function. Meanwhile, a layered parameter optimization method is proposed to fit with the structure of MMC-HVDC controller. The combined invocation and data interaction between MATLAB and PSCAD/EMTDC are implemented in this paper. Algorithm performance analysis and electromagnetic transient simulation results show that the proposed method converges fast and can obtain the uniform Pareto frontier. It can also improve the dynamic performance of the system effectively.