Research on size and location of distributed generation with vulnerable node identification in the active distribution network

被引:46
|
作者
Zhao, Yuanyuan [1 ]
An, Yiran [1 ]
Ai, Qian [1 ]
机构
[1] Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai 200240, Peoples R China
关键词
ALLOCATION; PLACEMENT;
D O I
10.1049/iet-gtd.2013.0887
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
This study aims to solve for the optimal location and capacity of distributed generation (DG), taking vulnerable node identification into consideration, in active distribution networks (ADN). Vulnerable nodes exist in the distribution network. Considering that the power fluctuations of those vulnerable nodes will have a significant impact on other nodes, the allocations of the DGs should avoid such nodes. Therefore vulnerable node identification and removal from the network can greatly limit the siting range of DGs. In this study, the vulnerable nodes are identified based on the small-world network theory, which is used as the preliminary location of the DG. Then, a genetic algorithm (GA) is proposed to finally address the optimal location and capacity for grid-connected DG. A GA with voltage boundary constraints is utilised to effectively prevent the bus voltage from reaching its boundary. This method improves the calculation efficiency greatly and is therefore suitable for flexible distribution network topology in ADN. According to the change of the distribution network topology, the corresponding optimal location and capacity limit for the DG can be quickly calculated. Some examples validate the algorithm and prove that it has fast convergence.
引用
收藏
页码:1801 / 1809
页数:9
相关论文
共 50 条
  • [31] Fault Location Method for Distribution Network with Distributed Generation Based on Deep Learning
    Liu, Shourui
    Yin, Hong
    Zhang, Yuan
    Liu, Xuan
    Li, Chunbo
    2022 4TH INTERNATIONAL CONFERENCE ON SMART POWER & INTERNET ENERGY SYSTEMS, SPIES, 2022, : 1157 - 1162
  • [32] Optimal Planning of Distributed Generation and Loads in Active Distribution Network:A Review
    Wang, Shichuan
    Sun, Yuanyuan
    Li, Yahui
    Li, Kejun
    An, Peng
    Yu, Guangyuan
    2020 4TH INTERNATIONAL CONFERENCE ON GREEN ENERGY AND APPLICATIONS (ICGEA 2020), 2020, : 176 - 181
  • [33] Active distribution network with efficient utilisation of distributed generation ancillary services
    Ampofo, Desmond O.
    Al-Hinai, Amer
    El Moursi, Mohamed
    IET SMART GRID, 2018, 1 (04) : 151 - 158
  • [34] Maximum Uncertainty Boundary of Volatile Distributed Generation in Active Distribution Network
    Wan, Can
    Lin, Jin
    Guo, Wanfang
    Song, Yonghua
    IEEE TRANSACTIONS ON SMART GRID, 2018, 9 (04) : 2930 - 2942
  • [35] A Novel Method for Islanding in Active Distribution Network Considering Distributed Generation
    Wang, Jun
    Wang, Xinran
    Di, Bart
    Sun, Chao
    Zheng, Wei
    JOURNAL OF POWER TECHNOLOGIES, 2021, 101 (01): : 11 - 20
  • [36] A Novel Method for Islanding in Active Distribution Network Considering Distributed Generation
    Wang, Jun
    Wang, Xinran
    Di, Bart
    Sun, Chao
    Zheng, Wei
    Journal of Power Technologies, 2021, 101 (01): : 11 - 20
  • [37] Active Distribution Network Expansion Planning Considering Distributed Generation Integration and Network Reconfiguration
    Xing, Haijun
    Hong, Shaoyun
    Sun, Xin
    JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, 2018, 13 (02) : 540 - 549
  • [38] Finding of the Probable Size and Location of Distributed Generation in Unbalanced Distribution System with Demand Uncertainty
    Jana, Chandan
    Bala, Mousumi Jana
    Goswami, Swapan Kumar
    2020 IEEE CALCUTTA CONFERENCE (CALCON), 2020, : 417 - 420
  • [39] MSFL Based Determination of Optimal Size and Location of Distributed Generation in Radial Distribution System
    Mistry, Khyati
    2016 INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONICS, AND OPTIMIZATION TECHNIQUES (ICEEOT), 2016, : 530 - 535
  • [40] Fault Location in Distribution Feeders with Distributed Generation
    Souto, Laiz
    Manassero Junior, Giovanni
    Di Santo, Silvio Giuseppe
    2016 CLEMSON UNIVERSITY POWER SYSTEMS CONFERENCE (PSC), 2016,