摘要
在光照不均匀情况下,光伏阵列P-V曲线上会出现多个极值点,传统算法容易陷入局部最优而失效。文中提出粒子群-细菌觅食算法,将粒子群算法和细菌觅食算法结合。用粒子群算法进行全局搜索,再将粒子看成细菌用细菌觅食算法进行局部搜索。仿真结果证明,该算法在多峰情况的快速准确性。
Under the condition of uneven illumination, many extreme value points will appear on the photovoltaic array P-V curve. The traditional algorithm may suffer from local optimization and become invalid. In this paper, the particle swarm-bacterial foraging algorithm is put forward, which combines the particle swarm optimization （pso） algorithm and the bacterial foraging algorithm. The particle swarm algorithm is used for global search and then the particles are seen as bacteria and the bacterial foraging algorithm is used for local search. Simulation results show that the algorithm is accurate and fast in multi-peak conditions.
出处
《电子科技》
2015年第5期114-117,共4页
Electronic Science and Technology
