基于历史数据聚类分析的暂态功角稳定故障筛选
作者:
中图分类号:

TM712

基金项目:

国家电网有限公司总部科技项目(52110418002A)


Transient power angle stability contingency screening based on clustering analysis of historical data
Author:
Fund Project:

Project supported by the State Grid Corporation of China Science Project(52110418002A)

  • 摘要
  • | |
  • 访问统计
  • |
  • 参考文献 [24]
  • |
  • 相似文献 [20]
  • | | |
  • 文章评论
    摘要:

    大电网中有上千个暂态稳定故障,若对每个故障分别进行暂态评估,难以满足在线评估对时间的要求。为了满足电网在线暂态安全稳定评估快速性的要求,提出了一种基于电网运行历史数据聚类分析的暂态功角稳定故障筛选方法。基于历史数据中的电网运行方式和暂态功角稳定评估结果,提取关键特征量,通过计及稳定模式的矢量量化方法确定聚类数和初始聚类中心,采用K中心点算法对聚类中心进行优化。针对分类后暂态功角稳定的考察故障快速估算其暂态功角裕度,最后得到包含暂态功角失稳和估算裕度低于门槛值的故障组成的用于暂态稳定分析计算的严重故障集。通过对实际省级电网运行历史数据的聚类分析,验证了所述方法的有效性和实用性。

    Abstract:

    There are thousands of transient stability faults in large scale power system. Transient stability analysis cannot be finished in given time required by online assessment. To meet the requirement of calculation time of on-line transient security and stabiliby assessment, an transient power angle security and stability contingency screening method base on clustering analysis of power grid operation history data.Extracting key feature quantities based on power grid operation mode and transient power angle stability assessment results in historical data.Determine the number of clusters and the initial clustering center by vector quantization method that takes into account the stable mode.Optimization of clustering center points using K-Medoids algorithm. The transient power angle margin is quickly estimated for the faults of the transient power angle stability after classification. Finally, a severe contingency set consisting of the faults of the transient power angle instability and the estimated margin below the threshold is obtained. According to the clustering analysis of actual history data, the validity and practicability fo the proposed method can be verified.

    参考文献
    [1] 刘俊, 孙惠文, 吴柳, 等. 电力系统暂态稳定性评估综述[J]. 智慧电力, 2019, 47(12):44-53, 122. LIU Jun, SUN Huiwen, WU Liu, et al. Overview of transient stability assessment of power systems[J]. Smart Power, 2019, 47(12):44-53, 122.
    [2] 潘明帅, 汪芳宗, 宋墩文, 等. 基于广义向后差分方法的电力系统暂态稳定性快速数值计算方法[J]. 电力系统保护与控制, 2018, 46(1):9-15. PAN Mingshuai, WANG Fangzong, SONG Dunwen, et al. Fast power system transient stability simulations by generalized backward differentiation formulae[J]. Power System Protection and Control, 2018, 46(1):9-15.
    [3] 谭炜东,汪芳宗. 一种新的电力系统暂态稳定性时间并行计算方法[J]. 广东电力,2018,31(9):129-134. TAN Weidong, WANG Fangzong. A new time parallel calcula-tion method for transient stability of power system[J]. Guangd-ong Electric Power,2018,31(9):129-134.
    [4] 徐泰山,薛禹胜,李碧君,等. 暂态稳定在线预警故障集的自适应筛选[J]. 电力系统自动化,2009, 33(22): 1-4. XU Taishan,XUE Yusheng,LI Bijun,et al. On-line adaptive contingency screening for early-waring of transient stability[J]. Automation of Electric Power Systems,2009, 33(22):1-4.
    [5] 傅旭, 李生, 张桂红, 等. 一种输电通道送电能力评估的新方法[J]. 智慧电力, 2019, 47(12):54-58, 84. FU Xu, LI Sheng, ZHANG Guihong, et al. A new method for evaluating power transmission capacity of transmission channels[J]. Smart Power, 2019, 47(12):54-58, 84.
    [6] 张乾, 胡雪凯, 李均强, 等. 基于复合功角及稳定裕度的多机系统分群研究[J]. 智慧电力, 2018, 46(7):56-60. ZHANG Qian, HU Xuekai, LI Junqiang, et al. Generator groups identification study based on complex angle and stability margin[J]. Smart Power, 2018, 46(7):56-60.
    [7] 常康, 徐泰山, 郁琛, 等. 自然灾害下电网运行风险控制策略探讨[J]. 电力系统保护与控制, 2019, 47(10):73-81. CHANG Kang, XU Taishan, YU Chen, et al. Discussion of power system operation risk control strategy in natural disasters[J]. Power System Protection and Control, 2019, 47(10):73-81.
    [8] 李碧君,许剑冰,徐泰山,等. 大电网安全稳定综合协调防御的工程应用[J]. 电力系统自动化,2008,32(6):25-30. LI Bijun,XU Jianbing,XU Taishan,et al. Engineering applica-tion of integrated and coordinated defense technology of large power system security and stability[J]. Automation of Electric Power Systems,2008,32(6):25-30.
    [9] 徐泰山,杜延菱,鲍颜红,等. 在线暂态安全稳定评估的分类滚动故障筛选方法[J]. 电力系统自动化,2018,42(13):182-188. XU Taishan,DU Yanling,BAO Yanhong,et al. A classification rolling contingency screening method for on-line transient secu-rity and stability assessment[J]. Automation of Electric Po-wer Systems,2018,42(13):182-188.
    [10] SUNITHA R,SREERAMA K, ABRAHAM T M. Online static security assessment module using artificial neural network[J]. IEEE Transactions on Power Systems,2013,28(4):4328-4335.
    [11] KAPLUNOVICH P A,TURITSYN K. Fast and reliable scr-een-ing of N-2 contingencies[J]. IEEE Transactions on Power Systems,2016,31(6):4243-4252.
    [12] 刘友波,刘洋,刘俊勇,等. 基于Hadoop架构的电力系统连锁故障分布式计算计算[J]. 电力系统自动化,2016,40(7):90-97. LIU Youbo,LIU Yang,LIU Junyong,et al. Hadoop based distributed computing framework for large-scale cascading failure simulation and analysis of power system[J]. Automation of Electric Power Systems,2016,40(7):90-97.
    [13] 薛禹胜,黄天罡,陈国平,等. 关于暂态稳定分析算例筛选的评述[J]. 电力系统自动化,2019,43(6): 1-14. XUE Yusheng,HUANG Tiangang,CHEN Guoping,et al. Re-vi-ew on case filtering in transient stability analysis[J]. Au-to-ma-tion of Electric Power Systems,2019, 43(6):1-14.
    [14] 徐泰山,鲍颜红,杨莹,等. N-2组合故障集的暂态功角稳定性在线快速评估[J]. 电力系统保护与控制,2015, 43(7):122-126. XU Taishan,BAO Yanhong,YANG Ying,et al. Online fast transient angle stability assessment of N-2 contingency set[J]. Power System Protection and Control,2015, 43(7):122-126.
    [15] 刘笙,汪静. 电力系统的暂态能量函数分析[M]. 上海: 上海交通大学出版社,1996. LIU Sheng, WANG Jing.Transient energy function analysis of power system[M]. Shanghai:Shanghai Jiaotong University Press, 1996.
    [16] 王成山,曹旌,陈光远. 基于聚类分析的电力系统暂态稳定故障筛选[J]. 电网技术,2005, 29(15):18-22. WANG Chengshan,CAO Jing,CHEN Guangyuan. Power sys-tem transient stability contingency screening based on cluste-ring analysis[J]. Power System Technology,2005, 29(15): 18-22.
    [17] 马翔匀,鲍颜红,张金龙,等. 基于支持向量机和决策函数的暂态稳定评估方法[J]. 电测与仪表,2018,20(9):1-7. MA Xiangyun,BAO Yanhong,ZHANG Jinlong,et al. Transient stability assessment based on support vector machine and decision function[J]. Electrical Measurement&Instrumentation,2018,20(9):1-7.
    [18] 汤必强,邓长虹,刘丽芳. 复合神经网络在电力系统暂态稳定评估中的应用[J]. 电网技术,2004,28(15):62-66. TANG Biqiang,DENG Changhon,LIU Lifang. Application of compound neural network in power system transient stability assessment[J]. Power System Technology,2004,28(15):62-66.
    [19] 孙宏斌,黄天恩,郭庆来,等. 基于仿真大数据的电网智能型超前安全预警技术[J]. 南方电网技术,2016,10(3):42-46. SUN Hongbin,HUANG Tianen,GUO Qinglai,et al. Power grid intelligent security early warning technology based on big simulation data[J]. Southern Power System Technology,2016, 10(3):42-46.
    [20] 马志昊,邵成平,余婷,等. 基于主成分分析的电力系统暂态特征提取[J]. 陕西电力,2013,12(5):5-13. MA Zhihao,SHAO Chengping,YU Ting,et al. PCA based transient feature extraction in power system[J]. Shannxi Electrical,2013,12(5):5-13.
    [21] 段青,赵建国,马艳. 基于优化的KPCA暂态稳定评估模型的特征提取[J]. 控制与决策,2010,25(9):1403-1407. DUAN Qing,ZHAO Jianguo,MA Yan. Feature extract based on optimized kernel principal component analysis in transient stability assessment[J]. Control and Decision,2010,25(9):1403-1407.
    [22] 向德军,王彬,郭文鑫,等. 基于人工神经网络的电力系统精细化安全运行原则[J]. 电力系统保护与控制,2017,45(18):32-37. XIANG Dejun,WANG Bin,GUO Wenxin,et al. Fine security rule for power system operation based on artificial neural network[J]. Power System Protection and Control,2017,45(18):32-37.
    [23] BEZDEK J C. Pattern recognition with fuzzy objective al-go-ri-thms[M]. New York:Plenum Press,1981.
    [24] 徐泰山,段荣华,鲍颜红,等. 基于预想故障集自动筛选的在线暂态安全稳定评估方法[P]. 云南:CN 107093895A,2017-08-25. XU Taishan,DUAN Ronghua,BAO Yanhong,et al. Online transient security stability assessment method based on automa-tic screening of expected fault set[P]. Yunnan:CN 1070938- 95A,2017-08-25.
    引证文献
    网友评论
    网友评论
    分享到微博
    发 布
引用本文

郭剑,朱炳铨,徐泰山,王胜明,徐雄峰.基于历史数据聚类分析的暂态功角稳定故障筛选[J].电力工程技术,2020,39(2):75-80

复制
分享
文章指标
  • 点击次数:1677
  • 下载次数: 2518
  • HTML阅读次数: 0
  • 引用次数: 0
历史
  • 收稿日期:2019-10-09
  • 最后修改日期:2019-11-13
  • 录用日期:2019-09-14
  • 在线发布日期: 2020-04-13
  • 出版日期: 2020-03-28
文章二维码