Power Losses Optimization of MMCs Based on Quantum Genetic Algorithm for HVdc Transmission Application

Abstract

Modular multilevel converters (MMCs) obtain widespread utilization in high-voltage direct current (HVdc) applications scenarios. The cost of power losses plays a significant part in MMC’s operating costs. Hence, this article proposes a quantum genetic algorithm-based power losses optimization control (QGA-PLOC). By comprehensively considering the power losses of the MMC, the quantum genetic algorithm determines the first-best value of the injected second circulating current magnitude and phase angle in the arm, as well as the optimal MMC power losses under given conditions. The quantum genetic algorithm incorporates the quantum state vector representation into genetic encoding and utilizes quantum logic gates for chromosome evolution, greatly improving the algorithm’s performance and significantly enhancing its computational efficiency and global optimization capability. Moreover, introducing the quantum genetic algorithm into the field of MMC power losses optimization offers a new path to address the acquisition of the optimal circulating current reference value in power loss optimization problems. MMC Simulation and experiment are also conducted, and the research results verify the effectiveness of the proposed QGA-PLOC for MMCs.