Research on NPC Three-Level Modulation Strategy Based on Quantum Genetic Algorithm

Power electronic converter technology, as the core support of energy conversion field, the optimization of its modulation strategy directly affects the system efficiency and power quality. NPC three-level converter is widely used in high-voltage high-power scenarios by virtue of the advantages of voltage stress equalization and output harmonic suppression. The traditional specific harmonic elimination pulse width modulation technique determines the switching angle by solving a system of nonlinear equations, but the dimension of the solution grows exponentially with the increase of the number of levels, and the conventional intelligent algorithms are prone to fall into the local optimum and limited convergence speed. The theory of quantum computing provides new ideas for solving complex optimization problems, and its superposition state characteristics can effectively enhance the diversity of the population, and the entanglement mechanism can accelerate the efficiency of information interaction. In this study, the quantum computing principle is deeply integrated with the traditional genetic algorithm, and a quantum genetic cooperative optimization framework is constructed to explore the switching angle optimization problem under multiple constraints. The hybrid algorithm breaks through the limitations of classical algorithms in solution space searching ability, and provides innovative solutions for high-dimensional nonlinear engineering optimization problems.