Impact of Higher-Order Structures in Power Grids' Graph on Line Outage Distribution Factor

被引:0
作者
Sadik, Nafis [1 ]
Narimani, Mohammad Rasoul [2 ]
机构
[1] Arkansas State Univ, Coll Engn & Comp Sci, Jonesboro, AR 72401 USA
[2] Calif State Univ Northridge CSUN, Dept Elect & Comp Engn, Northridge, CA USA
来源
2023 NORTH AMERICAN POWER SYMPOSIUM, NAPS | 2023年
关键词
DC load flow; Line outage distribution factor; Graph theory; Graphlets; COMPLEX;
D O I
10.1109/NAPS58826.2023.10318664
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
Power systems often include a specific set of lines that are crucial for the regular operations of the grid. Identifying the reasons behind the criticality of these lines is an important challenge in power system studies. When a line fails, the line outage distribution factor (LODF) quantifies the changes in power flow on the remaining lines. This paper proposes a network analysis from a local structural perspective to investigate the impact of local structural patterns in the underlying graph of power systems on the LODF of individual lines. In particular, we focus on graphlet analysis to determine the local structural properties of each line. This research analyzes potential connections between specific graphlets and the most critical lines based on their LODF. In this regard, we investigate N - 1 and N - 2 contingency analysis for various test cases and identifies the lines that have the greatest impact on the LODFs of other lines. We then determine which subgraphs contain the most significant lines. Our findings reveal that the most critical lines often belong to subgraphs with a less meshed but more radial structure. These findings are further validated through various test cases. Particularly, it is observed that networks with a higher percentage of ring or meshed subgraphs on their most important line (based on LODF) experience a lower LODF when that critical line is subject to an outage. Additionally, we investigate how the LODF of the most critical line varies among different test cases and examine the subgraph characteristics of those critical lines.
引用
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页数:6
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共 21 条
  • [1] Babaeinejadsarookolaee S, 2021, Arxiv, DOI arXiv:1908.02788
  • [2] Boyaci O, 2022, 3RD INTERNATIONAL CONFERENCE ON SMART GRID AND RENEWABLE ENERGY (SGRE), DOI [10.1109/SGRE53517.2022.9774040, 10.1109/SGRE533517.2022.9774040]
  • [3] Chen X., 2007, 2007 IEEE POW ENG SO, P1
  • [4] Generalized Injection Shift Factors
    Chen, Yu Christine
    Dhople, Sairaj V.
    Dominguez-Garcia, Alejandro D.
    Sauer, Peter W.
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2017, 8 (05) : 2071 - 2080
  • [5] Dey AK, 2017, IEEE GLOB CONF SIG, P1015, DOI 10.1109/GlobalSIP.2017.8309114
  • [6] BOUND ESTIMATES OF THE SEVERITY OF LINE OUTAGES IN POWER SYSTEM CONTINGENCY ANALYSIS AND RANKING
    GALIANA, FD
    [J]. IEEE TRANSACTIONS ON POWER APPARATUS AND SYSTEMS, 1984, 103 (09): : 2612 - 2624
  • [7] Identification of Vulnerable Lines in Smart Grid Systems Based on Affinity Propagation Clustering
    Gao, Qinghe
    Wang, Yawei
    Cheng, Xiuzhen
    Yu, Jiguo
    Chen, Xi
    Jing, Tao
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2019, 6 (03) : 5163 - 5171
  • [8] Generalized line outage distribution factors
    Guler, Teoman
    Gross, George
    Liu, Minghai
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2007, 22 (02) : 879 - 881
  • [9] Toward Efficient Wide-Area Identification of Multiple Element Contingencies in Power Systems
    Huang, Hao
    Mao, Zeyu
    Narimani, Mohammad Rasoul
    Davis, Katherine R.
    [J]. 2021 IEEE POWER & ENERGY SOCIETY INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE (ISGT), 2021,
  • [10] The 2015 Ukraine Blackout: Implications for False Data Injection Attacks
    Liang, Gaoqi
    Weller, Steven R.
    Zhao, Junhua
    Luo, Fengji
    Dong, Zhao Yang
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2017, 32 (04) : 3317 - 3318