基于免疫粒子群优化算法的微网谐波抑制方法

Harmonic Suppression Method for Micro-grid Based on Immune Particle Swarm Optimization Algorithm

微电网中逆变器等大量电力电子器件的应用,以及各种非线性负荷的投切,使微网中的谐波问题变得复杂。针对微网系统中滤波器参数难以整定导致微网谐波抑制效果受到影响的问题,提出了基于免疫粒子群算法的微网滤波器参数优化方法。建立了包含功率控制模块、下垂控制模块以及电压电流控制模块的基于下垂控制的微网系统模型,并根据微网性能以及滤波器参数设计特点建立了目标函数;对免疫粒子群算法能够避免粒子群算法陷入局部最优、解决早熟收敛等问题进行了介绍;提出了用免疫粒子群算法调用微网仿真系统优化参数的新方法;通过Matlab仿真验证了基于免疫粒子群算法的微网谐波抑制方法的可行性。

The application of a large number of power electronic devices and a variety of nonlinear load switching in micro-grid make harmonic problems complicated. In view of the problem that the difficultly in filter parameters tuning affects the effectiveness of micro-grid harmonic suppression, a method is proposed in this paper to optimize the micro-grid filter parameters by using the immune particle swarm optimization algorithm. Firstly, a droop control-based micro-grid model is established, which includes the power control module, voltage and culTent control module and droop control module, and an objective function is established based on micro-grid performance and filter parameters design features. Secondly, the immune particle swarm optimization algorithm is introduced to avoid the PSO getting into local optimization and to solve the premature convergence problem. The immune particle swarm algorithm, by introducing the concept of antibody concentration in immune algorithm into particle swarm optimization algorithm and replacing some of the individuals, can keep the diversity of population and jump out of local optimum Micro-grid filter parameter optimization is a multi-constraint and nonlinear optimization problem, This method can be used to obtain the appropriate filter parameters that meet the conditions. A new method is proposed to use the immune particle swarm optimization algorithm to call the micro-grid simulation system for optimizing parameters. In the end, the harmonic suppression method based on immune particle swarm optimization algorithm is proved to be feasible through MATLAB simulation of micro-grid.