基于SNDPSO的多峰值光伏最大功率追踪控制研究

Research on maximum power tracking control of multi peak photovoltaic based on SNDPSO

常规最大功率点追踪(MPPT)方法在光伏阵列局部阴影时,易陷入局部最优解从而追踪失败。提出了迭代步长呈正态分布衰减的粒子群算法(SNDPSO)。该算法中引入了最近邻学习过程,通过粒子相对距离的判断提高了最优解的精度,同时算法充分地将正态分布收敛速度快的优点和粒子群的全局峰值搜索能力结合起来。由仿真结果可知,SNDPSO算法在静态及动态阴影、均匀光照情况下均能实现快速精确的最大功率追踪。

The conventional MPPT method is easy to fall into the local optimal solution when the PV array is in local shadow,so the tracking fails.The particle swarm optimization algorithm with iteration step size normal distribution decay(SNDPSO)was proposed.The nearest neighbor learning process was introduced in the algorithm to improve the accuracy of the optimal solution by judging the relative distance of particles.The algorithm fully combined the fast convergence of the normal distribution with the global peak search ability of the particle swarm optimization simultaneously.The simulation results show that the new algorithm can achieve fast and accurate maximum power tracking under the conditions of static shadow,dynamic shadow and uniform illumination.