|
|
|
| Research of Global MPPT Algorithm of Photovoltaic Generation System based on FPA |
| Xue Pengfei1, Zhou Haifang1, Wang Mingjun2, Lin Peijie1 |
1. Fuzhou University College of Physics and Information Institute of Micro-Nano Devices and Solar Cells, Fuzhou 350116;
2. Wuhan Product Qualtiy Supervision and Testin Institute, Wuhan 430048 |
|
|
|
|
Abstract Traditional MPPT algorithm may fail under partially shaded conditions and global MPPT algorithms based on particle swarm optimization (PSO) has defects that parameter setting is complex and output oscillation is large. Pollen propagation algorithm (FPA) is a novel intelligent global swarm optimization algorithm, it has several advantages such as fast convergence, higher efficiency using fewer tuning parameters, good stability of results and so on. This paper proposes a MPPT algorithm based on FPA, set the parameters properly based on theoretical analysis and a large number of simulation studies. Contrastive simulations and experiments are carried out against FPA and PSO based MPPT algorithm. The results have shown that the developed algorithm can find the MPP effectively whether or not the illumination is uniform, moreover, FPA is better with respect to parameter settings, output power oscillation and convergence time.
|
|
Published: 23 May 2017
|
|
|
|
| Cite this article: |
|
Xue Pengfei,Zhou Haifang,Wang Mingjun等. Research of Global MPPT Algorithm of Photovoltaic Generation System based on FPA[J]. Electrical Engineering, 2017, 18(5): 1-5.
|
|
|
|
| URL: |
|
http://dqjs.cesmedia.cn/EN/Y2017/V18/I5/1
|
[1] 薛蕾, 赵建辉, 李帆, 等. 光伏系统多峰最大功率点跟踪法研究[J]. 太阳能学报, 2014, 35(8): 1422-1428.
[2] Benyoucef A S, Chouder A, Kara K A, et al. Artificial bee colony based algorithm for maximum power point tracking (MPPT) for PV systems operating under partial shaded conditions[J]. Applied Soft Computing, 2015(32): 38-48.
[3] Kulaksiz A A, Akkaya R. A genetic algorithm optimized ANN-based MPPT algorithm for a stand-alone PV system with induction motor drive[J]. Solar Energy, 2012, 86(9): 2366-2375.
[4] 朱艳伟, 石新春, 但扬清, 等. 粒子群优化算法在光伏阵列多峰最大功率点跟踪中的应用[J]. 中国电机工程学报, 2012, 32(4): 42-48.
[5] 张永革, 石季英, 张文, 等. 复杂遮阴时吞并式PSO算法在MPPT中的应用[J]. 电力电子技术, 2015, 49(2): 72-74.
[6] 娄贺伟, 李光林, 蔡鹏宇, 等. 改进粒子群算法在光伏阵列多峰值MPPT中的应用[J]. 自动化与仪器仪表, 2015(3): 193-195.
[7] Ahmed J, Salam Z. A maximum power point tracking (MPPT) for PV system using cuckoo search with partial shading capability[J]. Applied Energy, 2014(119): 118-130.
[8] Alam DF, Yousri DA, Eteiba MB. Flower pollination algorithm based solar PV parameterestimation[J]. Energy Conversion&Management, 2015(101): 410- 422.
[9] Yang X S. Flower pollination algorithm for global optimization[C]//Unconventional computation and natural computation. Berlin Heidelberg: Springer, 2012: 240-249. |
|
|
|
2017, Vol. 18 
