Power system transient stability assessment based on MVEE and LSPTSVM

被引:0
|
作者
Wang L. [1 ]
Han D. [2 ]
Wang C. [2 ]
Wei J. [3 ]
Li B. [4 ]
机构
[1] State Grid Liaoning Electric Power Supply Co., Ltd., Shenyang
[2] School of Electrical Engineering, Northeast Electric Power University, Jilin
[3] Northeast China Branch, Huadian Electric Power Research Institute Co., Ltd., Shenyang
[4] Electric Power Research Institute of State Grid Liaoning Electric Power Co., Ltd., Shenyang
关键词
Least square projection twin support vector machine; Minimum volume enclosing ellipsoid; Pattern recognition; Transient stability assessment;
D O I
10.19783/j.cnki.pspc.191244
中图分类号
学科分类号
摘要
Given the difficulties of constructing the feature set and the slow training speed of the evaluation model when using the pattern recognition method for power system transient stability assessment, a power system transient stability assessment method based on Minimum Volume Enclosing Ellipsoid (MVEE) and Least Square Projection Twin Support Vector Machine (LSPTSVM) is proposed. First, according to the MVEE theory, the system trajectory information is optimized to determine the minimum volume closure ellipsoid with all trajectory information in high dimensional space. We construct the input feature set using the physical properties of the minimum volume closure ellipsoid. This can effectively achieve feature set dimension reduction. Secondly, a regularization term is introduced into the objective function of the traditional projection twin support vector machine, and the internal constraints of the evaluation model are improved. This can improve the solution speed of the model and meet the computational efficiency requirements of large-scale power systems. Finally, the validity and feasibility of the proposed method are verified by the case analysis of IEEE-39 and IEEE-145 node systems. © 2020, Power System Protection and Control Press. All right reserved.
引用
收藏
页码:45 / 54
页数:9
相关论文
共 30 条
  • [1] LIANG Zhifeng, GE Rui, DONG Yu, Et al., Analysis of large-scale blackout occurred on July 30 and July 31, 2012 in India and its lessons to China's Power Grid dispatch and operation, Power System Technology, 37, 7, pp. 1841-1848, (2013)
  • [2] CHANG Kang, XU Taishan, YU Chen, Et al., Discussion of power system operation risk control strategy in natural disasters, Power System Protection and Control, 47, 10, pp. 73-81, (2019)
  • [3] XIN Jianbo, WANG Yulin, SHU Zhan, Et al., Transient stability impact analysis of UHV AC/DC access to Jiangxi power grid, Power System Protection and Control, 47, 8, pp. 71-79, (2019)
  • [4] CHEN Zhen, XIAO Xianyong, LI Changsong, Et al., Power system transient stability assessment based on cost-sensitive extreme learning machine, Electric Power Automation Equipment, 36, 2, pp. 118-123, (2016)
  • [5] GUAN Lin, HE Chuyao, ZENG Yihao, Et al., Intelligent stability assessment based on pattern recognition, Electric Power Automation Equipment, 36, 11, pp. 107-119, (2016)
  • [6] WANG Yajun, WANG Bo, TANG Fei, Et al., Power system online transient stability assessment based on response trajectory and core vector machine, Proceedings of the CSEE, 34, 19, pp. 3178-3186, (2014)
  • [7] JIANG Tao, WANG Changjiang, CHEN Houhe, Et al., Transient stability assessment of power system based on projection twin support vector machine with regularization, Automation of Electric Power Systems, 43, 1, pp. 141-148, (2019)
  • [8] YAO Dequan, JIA Hongjie, ZHAO Shuai, Power system transient stability assessment and stability margin prediction based on compound neural network, Automation of Electric Power Systems, 37, 20, pp. 41-46, (2013)
  • [9] SHAO Yaning, TANG Fei, LIU Dichen, Et al., An approach of transient angle stability assessment in power system for WAMS measured data, Power System Protection and Control, 43, 6, pp. 33-39, (2015)
  • [10] ZHANG Weiling, HU Wei, MIN Yong, Et al., Conservative online transient stability assessment in power system based on concept of stability region, Power System Technology, 40, 4, pp. 992-998, (2016)