A Reconfiguration Method for Regional Distribution Networks with Graph-based Ant System

被引：0
|
作者：
Sun, Yuanbo [1 ]
Zhang, Chengxue [1 ]
Hu, Zhijian [1 ]
机构：
[1] Wuhan Univ, Sch Elect Engn, Wuhan 430072, Peoples R China
来源：
PROCEEDINGS 2013 INTERNATIONAL CONFERENCE ON MECHATRONIC SCIENCES, ELECTRIC ENGINEERING AND COMPUTER (MEC) | 2013年
关键词：
regional distribution networks; reconfiguration; graph-based ant system; graph theory;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The graph-based ant system method is used for solving reconfiguration problem in regional distribution networks. The solution process includes an off-line part and an on-line part. The off-line part analyses topology. Route graph is used for expressing the feasible solution set. The online part searches the best solution by simulating the ants' traveling in route graph. Since the feasible solution set is large, this paper modifies the rules of route selection and pheromone updating to avoid the searching process falling into stagnation. Simulation example using an actual regional distribution networks indicates the method's effectiveness.
引用
收藏
页码：3705 / 3708
页数：4
相关论文
共 50 条
  • [21] GraphHO: A Graph-based Handover Optimization System for Cellular Networks
    Yang, Lin
    Cheng, Min
    Qiu, Jun
    Chen, Zhitang
    2022 INTERNATIONAL SYMPOSIUM ON WIRELESS COMMUNICATION SYSTEMS, ISWCS, 2022,
  • [22] Reconfiguration and fault restoration of regional distribution networks
    Sun, Yuanbo
    Zhang, Chengxue
    Hu, Zhijian
    Dianwang Jishu/Power System Technology, 2014, 38 (12): : 3366 - 3371
  • [23] Graph-Based Learning for Leak Detection and Localisation in Water Distribution Networks
    Gardarsson, Gardar Orn
    Boem, Francesca
    Toni, Laura
    IFAC PAPERSONLINE, 2022, 55 (06): : 661 - 666
  • [24] A Graph-Based Hybrid Reconfiguration Deformation Planning for Modular Robots
    Wei, Ruopeng
    Liu, Yubin
    Dong, Huijuan
    Zhu, Yanhe
    Zhao, Jie
    SENSORS, 2023, 23 (18)
  • [25] Graph-Based Global Reasoning Networks
    Chen, Yunpeng
    Rohrbach, Marcus
    Yan, Zhicheng
    Yan, Shuicheng
    Feng, Jiashi
    Kalantidis, Yannis
    2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019), 2019, : 433 - 442
  • [26] Hybrid graph-based networks for multiprocessing
    Dharma P. Agrawal
    Chienhua Chen
    J. Richard Burke
    Telecommunication Systems, 1998, 10 : 107 - 134
  • [27] GRAPH-BASED RECOMMENDATION SYSTEM
    Yang, Kaige
    Toni, Laura
    2018 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP 2018), 2018, : 798 - 802
  • [28] Graph-Based Motion Planning Networks
    Tai Hoang
    Ngo Anh Vien
    MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2020, PT II, 2021, 12458 : 557 - 573
  • [29] Graph-based analysis of metabolic networks
    van Helden, J
    Wernisch, L
    Gilbert, D
    Wodak, SJ
    BIOINFORMATICS AND GENOME ANALYSIS, 2002, 38 : 245 - 274
  • [30] Hybrid graph-based networks for multiprocessing
    Agrawal, DP
    Chen, CH
    Burke, JR
    TELECOMMUNICATION SYSTEMS, 1998, 10 (1-2) : 107 - 134
12345