局部阴影下基于遗传蚁群算法对MPPT的研究

发布时间：2018-01-07 03:39

本文关键词：局部阴影下基于遗传蚁群算法对MPPT的研究　出处：《可再生能源》2017年01期 　论文类型：期刊论文

【摘要】：针对光伏阵列局部遮挡时P-V特性曲线存在多个峰值的情况,以最大功率跟踪点为研究对象,提出基于遗传蚁群算法的MPPT算法,该算法基于遗传算法的计算理念,通过引入蚁群算法中信息素累积的概念,将两种算法进行有效融合,解决了遗传算法寻优效率低的问题。文章对基于遗传蚁群算法的MPPT算法进行建模、仿真。研究结果表明:在仿真计算中,与遗传算法相比,基于遗传蚁群算法的MPPT算法在收敛速度和精确性方面均有明显提高;在实际工程应用中,与遗传算法相比,基于遗传蚁群算法的MPPT算法不仅可以稳定跟踪到最大功率点,而且跟踪用时缩减了80%。
[Abstract]:Aiming at the multi-peak value of P-V characteristic curve in local occlusion of photovoltaic array, the MPPT algorithm based on genetic ant colony algorithm is proposed, which takes the maximum power tracking point as the research object. Based on the computational concept of genetic algorithm, the two algorithms are effectively fused by introducing the concept of pheromone accumulation in ant colony algorithm. In this paper, the MPPT algorithm based on genetic ant colony algorithm is modeled and simulated. The research results show that: in the simulation calculation, compared with genetic algorithm. The convergence speed and accuracy of MPPT algorithm based on genetic ant colony algorithm are improved obviously. Compared with the genetic algorithm, the MPPT algorithm based on genetic ant colony algorithm can not only track the maximum power point stably, but also reduce the tracking time by 80%.
【作者单位】：西安建筑科技大学机电工程学院;
【基金】：陕西省教育厅科研基金(11JK0875)
【分类号】：TM615;TP18
【正文快照】： 0引言最终会导致跟踪失败。随着国家经济的快速增长,电力需求日益增针对上述问题,本文提出一种基于遗传蚁群强。对于传统发电工艺而言,能源危机和环境污染算法的MPPT算法,将蚁群算法和遗传算法在不问题日趋严重。丰富的太阳能资源逐渐成为各国同运算阶段的优点进行结合,优势互

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