Particle Swarm Optimization for Outdoor Lighting Design

被引:7
|
作者
Castillo-Martinez, Ana [1 ]
Almagro, Jose Ramon [2 ]
Gutierrez-Escolar, Alberto [1 ]
del Corte, Antonio [1 ]
Luis Castillo-Sequera, Jose [1 ]
Manuel Gomez-Pulido, Jose [1 ]
Gutierrez-Martinez, Jose-Maria [1 ]
机构
[1] Univ Alcala, Polytech Sch, Dept Comp Sci, Madrid Barcelona Rd,Km 33-6, Alcala De Henares 28871, Spain
[2] Airbus Def & Space, Gunnels Wood Rd, Stevenage SG12AS, Herts, England
关键词
Energy efficiency; lighting design; lighting optimization; particle swarm optimization (PSO);
D O I
10.3390/en10010141
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Outdoor lighting is an essential service for modern life. However, the high influence of this type of facility on energy consumption makes it necessary to take extra care in the design phase. Therefore, this manuscript describes an algorithm to help light designers to get, in an easy way, the best configuration parameters and to improve energy efficiency, while ensuring a minimum level of overall uniformity. To make this possible, we used a particle swarm optimization (PSO) algorithm. These algorithms are well established, and are simple and effective to solve optimization problems. To take into account the most influential parameters on lighting and energy efficiency, 500 simulations were performed using DIALux software (4.10.0.2, DIAL, Ludenscheid, Germany). Next, the relation between these parameters was studied using to data mining software. Subsequently, we conducted two experiments for setting parameters that enabled the best configuration algorithm in order to improve efficiency in the proposed process optimization.
引用
收藏
页数:11
相关论文
共 50 条
  • [21] Design and Optimization of Nonlinear Tapers using Particle Swarm Optimization
    Narendra Chauhan
    Ankush Mittal
    Dietmar Wagner
    M. V. Kartikeyan
    M. K. Thumm
    International Journal of Infrared and Millimeter Waves, 2008, 29 : 792 - 798
  • [22] Street lighting efficiency with particle swarm optimization algorithm following Indonesian standard
    Eriyadi, M.
    Abdullah, A. G.
    Mulia, S. B.
    Hasbullah, H.
    4TH ANNUAL APPLIED SCIENCE AND ENGINEERING CONFERENCE, 2019, 2019, 1402
  • [23] Visualizing particle swarm optimization - Gaussian particle swarm optimization
    Secrest, BR
    Lamont, GB
    PROCEEDINGS OF THE 2003 IEEE SWARM INTELLIGENCE SYMPOSIUM (SIS 03), 2003, : 198 - 204
  • [24] Optimization of Indoor Luminaire Layout for General Lighting Scheme Using Improved Particle Swarm Optimization
    Qu, Ji-Qing
    Xu, Qi-Lin
    Sun, Ke-Xue
    ENERGIES, 2022, 15 (04)
  • [25] Particle swarm optimization for worst case tolerance design
    Steiner, G
    Watzenig, D
    2003 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY, VOLS 1 AND 2, PROCEEDINGS, 2003, : 78 - 82
  • [26] Particle swarm optimization for optimal product line design
    Tsafarakis, Stelios
    Marinakis, Yannis
    Matsatsinis, Nikolaos
    INTERNATIONAL JOURNAL OF RESEARCH IN MARKETING, 2011, 28 (01) : 13 - 22
  • [27] Circuit Design Based on Particle Swarm Optimization Algorithms
    Yan Xuesong
    Wu Qinghua
    Hu Chengyu
    Liang Qingzhong
    ADVANCED MATERIALS AND COMPUTER SCIENCE, PTS 1-3, 2011, 474-476 : 1093 - +
  • [28] Design of Particle Swarm Optimization with Random Flying Time
    Wang, Fujun
    Hong, Long
    2012 IEEE FIFTH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE (ICACI), 2012, : 346 - 349
  • [29] Design of dispersive multilayer with particle swarm optimization method
    Luo, Zhenyue
    Shen, Weidong
    Liu, Xu
    Gu, Peifu
    Xia, Cen
    CHINESE OPTICS LETTERS, 2010, 8 (03) : 342 - 344
  • [30] Design of dispersive multilayer with particle swarm optimization method
    罗震岳
    沈伟东
    刘旭
    顾培夫
    夏梣
    ChineseOpticsLetters, 2010, 8 (03) : 342 - 344