On Implementing a Spectral Clustering Controlled Islanding Algorithm in Real Power Systems

被引:0
|
作者
Demetriou, Panayiotis [1 ]
Kyriakides, Elias [1 ]
Quiros-Tortos, Jairo [2 ]
Terzija, Vladimir [2 ]
机构
[1] Univ Cyprus, Dept Elect & Comp Engn, Nicosia, Cyprus
[2] Univ Manchester, Sch Elect & Elect Engn, Manchester, Lancs, England
关键词
Controlled islanding; generator coherency; practical issues; robust clustering; spectral clustering; SPLITTING STRATEGIES; OPERATION;
D O I
暂无
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
Wide area blackouts can be caused by unexpected fault scenarios, in particular protection maloperation, or simultaneous low probability events, which as such might lead to e.g., un-damped electromechanical oscillations. A Spectral Clustering Controlled Islanding (SCCI) method to find a suitable islanding solution for preventing such events was previously proposed and tested using different IEEE test networks. The sole constraint applied to this solution was related to generator coherency. The method demonstrated promising results when it was implemented on these IEEE test networks. The SCCI method was later tested using a simplified Cypriot Network and the Polish Network. The results achieved when implementing the SCCI method on actual power systems highlight practical issues that were not previously considered and require to be addressed when using it. Therefore, this paper presents a robust SCCI method. An outlier problem which affects the quality of clustering and a problem with the computational efficiency of the algorithm (when dealing with systems larger than 500 nodes) are presented and analyzed in this paper. To improve the clustering quality, a more robust clustering algorithm, k-medoids, is used to cluster all nodes in the solution subspace and to find the islanding solution.
引用
收藏
页数:6
相关论文
共 50 条
  • [41] Generalised strategy for implementing the minimum fault reactance based fault location algorithm in real power distribution systems
    Correa-Tapasco, E.
    Mora-Florez, J.
    Perez-Londono, S.
    INGENIERIA E INVESTIGACION, 2011, 31 : 71 - 75
  • [42] Islanding detection using proportional power spectral density
    Yin, Jun
    Diduch, Chris Peter
    Chang, Liucheng
    IEEE TRANSACTIONS ON POWER DELIVERY, 2008, 23 (02) : 776 - 784
  • [43] Power time series curve clustering method combining improved spectral clustering and genetic algorithm
    Ding M.
    Huang F.
    Zou J.
    Liu J.
    Song X.
    Dianli Zidonghua Shebei/Electric Power Automation Equipment, 2019, 39 (02): : 93 - 99and114
  • [44] Optimal Islanding for Restoration of Power Distribution Systems Using Prim's MST Algorithm
    Sanaullah, Kaka
    Xia, Mingchao
    Hussain, Mazhar
    Hussain, Sharafat
    Tahir, Ammar
    CSEE JOURNAL OF POWER AND ENERGY SYSTEMS, 2022, 8 (02) : 599 - 608
  • [45] A new intelligent wide area controlled islanding detection method in interconnected power systems
    Isazadeh, Ghader
    Khodabakhshian, Amin
    Gholipour, Eskandar
    INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS, 2017, 27 (07):
  • [46] An Efficient Controlled Islanding Strategy for Large-Scale AC/DC Power Systems
    Song, Changcheng
    Chu, Xiaodong
    Ma, Linlin
    Wang, Xiaobo
    Li, Xin
    Wang, Liang
    Zhang, Bing
    Wu, Cheng
    ENERGIES, 2018, 11 (06)
  • [47] An adaptive spectral clustering algorithm
    College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China
    J. Comput. Inf. Syst., 2012, 2 (895-904):
  • [48] A review on intentional controlled islanding in smart power systems and generalized framework for ICI in microgrids
    Ahangar, Amir Reza Hassani
    Gharehpetian, Gevork B.
    Baghaee, Hamid Reza
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2020, 118 (118)
  • [49] An Improved Algorithm On Spectral Clustering
    Lihong
    Zhong Caiming
    2011 INTERNATIONAL CONFERENCE ON ELECTRONICS, COMMUNICATIONS AND CONTROL (ICECC), 2011, : 140 - 144
  • [50] A genetic spectral clustering algorithm
    Wang, Huiqing
    Chen, Junjie
    Guo, Kai
    Journal of Computational Information Systems, 2011, 7 (09): : 3245 - 3252