Multi-objective particle swarm optimization on ultra-thin silicon solar cells

被引:2
|
作者
Atalay, Ipek Anil [1 ]
Gunes, Hasan Alper [1 ]
Alpkilic, Ahmet Mesut [1 ]
Kurt, Hamza [1 ]
机构
[1] TOBB Univ Econ & Technol, Dept Elect & Elect Engn, TR-06560 Ankara, Turkey
来源
JOURNAL OF OPTICS-INDIA | 2020年 / 49卷 / 04期
关键词
Solar cells; Anti-reflection; Absorption enhancement; Surface texturing; Light trapping; Multi-objective particle swarm optimization; ABSORPTION ENHANCEMENT; ANTIREFLECTION; FABRICATION; LITHOGRAPHY;
D O I
10.1007/s12596-020-00653-z
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Finding optimized parameters for any photonic device is a challenging problem, because as the search space enlarges the computation time and design complexity increase. For higher performance solar cells, various studies have been carried out to procure optimized parameters, to attain better performance and low cost as well. In this study, we used a multi-objective particle swarm optimization approach to search design space effectively and obtain fixed parameters for enhanced solar spectrum absorption. Numerical investigations are conducted for pyramid surface pattern, to find proper solar cell parameters for minimum reflection and maximum light trapping which give rise to enhanced absorption of photons. For the ultra-thin-film silicon solar cell having a thickness of 1 mu m, a designed double-sided pyramid structure provides an ideal short-circuit photocurrent of 34.23 mA/cm(2). In this regard, the proposed approach can be applied to different film thicknesses of semiconductors for different photonic applications by manipulating the reflection/transmission coefficient and light trapping mechanism.
引用
收藏
页码:446 / 454
页数:9
相关论文
共 50 条
  • [1] Multi-objective particle swarm optimization on ultra-thin silicon solar cells
    Ipek Anil Atalay
    Hasan Alper Gunes
    Ahmet Mesut Alpkilic
    Hamza Kurt
    Journal of Optics, 2020, 49 : 446 - 454
  • [2] Integrated Optimization by Multi-Objective Particle Swarm Optimization
    Kawarabayashi, Masaru
    Tsuchiya, Junichi
    Yasuda, Keiichiro
    IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING, 2010, 5 (01) : 79 - 81
  • [3] Integrated optimization by multi-objective particle swarm optimization
    Tokyo Metropolitan University, 1-1, Minamiosawa, Hachioji-shi, Tokyo 192-0397, Japan
    IEEJ Trans. Electr. Electron. Eng., 1931, 1 (79-81):
  • [4] An Improved Multi-objective Particle Swarm Optimization
    Xu, Shengbing
    Ouyang, Zhiping
    Feng, Jiqiang
    2020 5TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND APPLICATIONS (ICCIA 2020), 2020, : 19 - 23
  • [5] A Particle Swarm Optimizer for Multi-Objective Optimization
    Cagnina, Leticia
    Esquivel, Susana
    Coello Coello, Carlos A.
    JOURNAL OF COMPUTER SCIENCE & TECHNOLOGY, 2005, 5 (04): : 204 - 210
  • [6] An Improving Multi-Objective Particle Swarm Optimization
    Fan, JiShan
    WEB INFORMATION SYSTEMS AND MINING, 2010, 6318 : 1 - 6
  • [7] An Improved Multi-Objective Particle Swarm Optimization
    Yang, Xixiang
    Zhang, Weihua
    ADVANCED SCIENCE LETTERS, 2011, 4 (4-5) : 1491 - 1495
  • [8] Modified Multi-Objective Particle Swarm Optimization Algorithm for Multi-objective Optimization Problems
    Qiao, Ying
    ADVANCES IN SWARM INTELLIGENCE, ICSI 2012, PT I, 2012, 7331 : 520 - 527
  • [9] Optimization of SIS solar cells with ultra-thin silicon oxide layer
    Song, X. M.
    Ye, C. Y.
    Huang, Z. G.
    FRONTIERS IN ENERGY RESEARCH, 2023, 11
  • [10] Dynamic Multi-Swarm Particle Swarm Optimization for Multi-Objective Optimization Problems
    Liang, J. J.
    Qu, B. Y.
    Suganthan, P. N.
    Niu, B.
    2012 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2012,