基于MPSO算法的特定谐波消除技术研究

目的 对于级联H桥逆变器的调制，特定谐波消除技术具有开关损耗小，能够消除特定次谐波，变换效率高等优点，但传统粒子群优化算法(Particle Swarm Optimization, PSO)在求解消谐方程组时收敛性差，容易局部最优，提出一种改进的粒子群优化算法(Modified Particle Swarm Optimization, MPSO)。方法 该算法用非线性惯性权重取代线性变化的惯性权重，并在非线性惯性权重引入混沌映射以产生随机性更好的随机量，新的惯性权重可权衡粒子的全局搜索和局部搜索能力，使粒子具有后期跳出局部最优的能力；另外，该算法优化了速度和位置的更新机制，以增强算法的收敛速度，并保证粒子在后期仍具有一定种群多样性优势。结果 根据级联H桥型逆变器的非线性消谐方程组，在保证输出电压基波的前提下最大化降低目标次谐波，建立适应度函数，将MPSO算法应用于级联H桥型逆变器的SHEPWM,能够在1～1.2的调制度范围内得到优化的开关角，提高收敛精度和求解成功率。通过七电平CHB逆变器仿真平台验证了MPSO算法所求的优化开关角能够有效地消除5次、7次谐波。结论 通过使用非线性惯性权...

Research on Selective Harmonic Elimination Technology Based on MPSO Algorithm

Objective Regarding the modulation of cascaded H-bridge inverter the selective harmonic elimination technology has the advantages of low switching loss elimination of specific subharmonics and high transformation efficiency. However the traditional particle swarm optimization PSO algorithm has poor convergence and is easy to be locally optimized when solving harmonic elimination equations. A modified particle swarm optimization MPSO algorithm was proposed. Methods In this algorithm the nonlinear inertia weight was used to replace the linear inertia weight and chaotic mapping was introduced into the nonlinear inertia weight to produce the random quantity with better randomness. The new inertia weight can balance the global search ability and local search ability of particles so that particles have the ability to jump out of the local optimum in the late stage. In addition the algorithm optimized the updating mechanism of speed and position to enhance the convergence speed of the algorithm and to ensure that the particles still have a certain population diversity advantage in the later stage. Results According to the nonlinear harmonic elimination equations of cascaded H-bridge inverter the fitness function was established to ensure the maximum reduction of the target harmonic under the premise of the output voltage base wave. When applied to SHEPWM of cascaded H-bridge inverter MPSO algorithm obtained optimized switching angle in the range of 1 ~ 1. 2 adjustment system. Compared with the PSO algorithm MPSO can improve the convergence accuracy and solving success rate. The seven-level CHB inverter simulation platform verified that the optimized switching angle obtained by MPSO algorithm can effectively eliminate the 5th and 7th harmonics. Conclusion By using the nonlinear inertia weight optimizing the velocity of particles and applying position update mechanism of particles the success rate of switch angle solution can be increased and the obtained solution can effectively eliminate the target subharmonics.