基于Copula传递熵的设备级和网络级宽频振荡传播路径分析及振荡源定位方法

doi:10.19595/j.cnki.1000-6753.tces.230873

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摘要

电力电子化电力系统的宽频振荡问题严重危害电网的安全稳定运行,及时确定宽频振荡的传播路径和振荡源位置,对振荡的抑制至关重要。本文从因果关系的角度提出一种基于Copula传递熵的设备级和网络级宽频振荡传播路径分析及振荡源定位方法,通过分析多变量之间的因果传递方向和因果强度系数,利用有向加权图构建宽频振荡因果网络,在此基础上确定振荡源位置,并通过保留因果强度系数最大的支路,确定振荡的主要传播路径。采用所提方法一方面能够从设备级分析控制器内部各状态变量的因果关联性,另一方面能够从网络级分析电网中各节点振荡数据的因果传递性,从而确定宽频振荡在控制器内部和电网中的传播路径及振荡源位置。最后,在强迫振荡、风机与弱电网交互、发电机轴系振荡中的仿真算例表明所提方法适用于多种机理的宽频振荡,能够同时实现设备级和网络级宽频振荡传播路径分析和振荡源定位。

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关键词 ：宽频振荡, 振荡传播, 振荡源定位, Copula传递熵, 因果分析

Abstract：

Wideband oscillations in the power electronic power system seriously endangers the safe and stable operation of the power grid. Timely determination of the propagation path and source location of wideband oscillations is crucial for suppressing oscillations. Model based analysis methods have limitations such as unknown parameters and high complexity, restaining their wide application in practical power systems. With the development of information theory, the method based on mathematical statistics becomes a promising method for the analysis of wideband oscillations. These methods focus on the correlation between data items and discover the inherent laws of wideband oscillations. Considering that the data of wideband oscillations in the new-generation power system is a multivariable strongly nonlinear and causal time series, it is worth conducting in-depth research on how to analyze the propagation characteristics of wideband oscillations and achieve oscillations source localization from the perspective of causal relationships based on mathematical statistics. Therefore, this article proposes a device and network level wideband oscillations propagation path analysis and oscillations source localization method based on Copula transfer entropy from the perspective of causality.
Firstly, the zero-mean normalization method is used to preprocess the analyzed oscillations data. Secondly, the original signal can be decomposed into a series of intrinsic mode components and a residual component using empirical mode decomposition (EMD). The residual component can be removed as it is independent of oscillations. Thirdly, for each mode, calculate the Copula transfer entropy between each variable to determine the direction of causal transfer. Then define the numerical value of Copula transfer entropy as the causal strength coefficient. Fourthly, a wideband oscillations causal network is constructed using directed weighted graphs, where each node in the network is a state variable or bus power signal, and the edge weights between each node are the causal strength coefficients between the corresponding variables. Fifthly, calculate the out-degree of each node in the network, and the node with the highest out-degree is determined as the position of the oscillations source. Finally, starting from the state variable or bus where the oscillations source is located, retain the branch with the highest causal strength coefficient, which is the main propagation path of the oscillation mode. At device level, the causal relationship between state variables within the controller can be revealed, thereby determining the key state variable and oscillations propagation path. At network level, the causal relationship between the power of each bus in the power grid can be revealed, and then the bus where the oscillations source is located and the oscillations propagation path can be determined.
On one hand, a simulation example of PMSG connected to grid is used to analyze the causal relationship of oscillations in various links within the controller. The propagation path diagram of the internal oscillations of the PMSG is obtained using the method proposed in this article. The sub synchronous oscillation mode of the system is mainly related to the DC capacitor link, outer voltage loop, and inner current loop of the PMSG. These links form the internal propagation path of this oscillation mode.
On the other hand, a simulation example of a four-machine two-area system containing a wind farm is used to analyze the causal relationship of oscillations between the busbars of a complex system. Simulation examples in forced oscillations, interaction between wind turbines and weak grid, and generator shaft system oscillations demonstrate that the proposed method is suitable for various mechanisms of wideband oscillations, and can achieve wideband oscillations propagation path analysis and oscillations source localization from the network level.
The following conclusions can be drawn from the simulation analysis:（1）The method based on Copula transfer entropy avoids establishing a detailed model, and its simulation results are consistent with the oscillations propagation path obtained from theoretical derivation. (2) The method is suitable for various mechanisms of wideband oscillations such as forced oscillations, interaction between wind turbines and weak grid, and generator shaft system oscillations. (3) The method can simultaneously achieve wideband oscillations propagation path analysis and oscillations source localization at device and network level.

Key words： Wideband oscillations oscillations propagation oscillations source localization Copula transfer entropy causal analysis

收稿日期: 2023-06-07

PACS:

TM712

基金资助:

国家自然科学基金资助项目（52377084,52007028）

通讯作者: 冯双女,1990年生,副教授,博士生导师,研究方向电力电子化电力系统分析与控制、人工智能技术在电力系统中的应用。E-mail：sfeng@seu.edu.cn

作者简介: 杨浩男,1998年生,硕士研究生,研究方向为基于量测数据的电力系统宽频振荡分析。E-mail：yang_hao_@seu.edu.cn

引用本文:

冯双, 杨浩, 崔昊, 汤奕, 雷家兴. 基于Copula传递熵的设备级和网络级宽频振荡传播路径分析及振荡源定位方法[J]. 电工技术学报, 0, (): 230873-230873. Feng Shuang, Yang Hao, Cui Hao, Tang Yi, Lei Jiaxing. Device and Network Level Wideband Oscillations Propagation Path Analysis and Source Localization Method Based on Copula Transfer Entropy. Transactions of China Electrotechnical Society, 0, (): 230873-230873.

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https://dgjsxb.ces-transaction.com/CN/10.19595/j.cnki.1000-6753.tces.230873 https://dgjsxb.ces-transaction.com/CN/Y0/V/I/230873

[1] 樊肖杰, 迟永宁, 马士聪, 等. 大规模海上风电接入电网关键技术与技术标准的研究及应用[J]. 电网技术, 2022, 46(8): 2859-2870.
Fan Xiaojie, Chi Yongning, Ma Shicong, et al.Research and application of key technologies and technical standards for large-scale offshore wind farms connecting to power grid[J]. Power System Technology, 2022, 46(8): 2859-2870.
[2] 饶宏, 周月宾, 李巍巍, 等. 柔性直流输电技术的工程应用和发展展望[J]. 电力系统自动化, 2023, 47(1): 1-11.
Rao Hong, Zhou Yuebin, Li Weiwei, et al.Engineering application and development prospect of VSC-HVDC transmission technology[J]. Automation of Electric Power Systems, 2023, 47(1): 1-11.
[3] Wang Xiongfei, Blaabjerg F.Harmonic stability in power electronic-based power systems: concept, modeling, and analysis[J]. IEEE Transactions on Smart Grid, 2018, 10(3): 2858-2870.
[4] 孙华东, 徐式蕴, 许涛, 等. 电力系统安全稳定性的定义与分类探析[J]. 中国电机工程学报, 2022, 42(21): 7796-7809.
Sun Huadong, Xu Shiyun, Xu Tao, et al.Research on definition and classification of power system security and stability[J]. Proceedings of the CSEE, 2022, 42(21): 7796-7809.
[5] Liu Huakun, Xie Xiaorong, He Jingbo, et al.Subsynchronous interaction between direct-drive PMSG based wind farms and weak AC networks[J]. IEEE Transactions on Power Systems, 2017, 32(6): 4708-4720.
[6] 黄碧月. 直驱风电并网的电力系统动态特性分析与次同步振荡研究[D]. 武汉: 华中科技大学, 2021.
[7] 高本锋, 王义, 曾四鸣, 等. 直驱风电场并入弱交流电网的次同步分量通路及阻尼特性分析[J]. 中国电机工程学报, 2022, 42(14): 5089-5103.
Gao Benfeng, Wang Yi, Zeng Siming, et al.Analysis of sub-synchronous component path and damping characteristics of D-PMSG-based wind farm incorporated into weak AC grid[J]. Proceedings of the CSEE, 2022, 42(14): 5089-5103.
[8] 王利超, 于永军, 张明远, 等. 直驱风电机组阻抗建模及次同步振荡影响因素分析[J]. 电力工程技术, 2020, 39(1): 170-177.
Wang Lichao, Yu Yongjun, Zhang Mingyuan, et al.Impedance model and analysis of subsynchronous oscillation influence factors for grid-connected full-converter wind turbines[J]. Electric Power Engineering Technology, 2020, 39(1): 170-177.
[9] 马宁宁, 谢小荣, 贺静波, 等. 高比例新能源和电力电子设备电力系统的宽频振荡研究综述[J]. 中国电机工程学报, 2020, 40(15): 4720-4732.
Ma Ningning, Xie Xiaorong, He Jingbo, et al.Review of wide-band oscillation in renewable and power electronics highly integrated power systems[J]. Proceedings of the CSEE, 2020, 40(15): 4720-4732.
[10] Gu Kanghui, Wu Feng, Zhang Xiaoping.Sub-synchronous interactions in power systems with wind turbines: a review[J]. IET Renewable Power Generation, 2019, 13(1): 4-15.
[11] 朱茂林, 刘灏, 毕天姝. 考虑风电场量测相关性的双馈风力发电机鲁棒动态状态估计[J]. 电工技术学报, 2023, 38(3): 726-740.
Zhu Maolin, Liu Hao, Bi Tianshu.Robust dynamic state estimation of doubly-fed induction generator considering measurement correlation in wind farms[J]. Transactions of China Electrotechnical Society, 2023, 38(3): 726-740.
[12] Xie Xiaorong, Zhan Ying, Shair J, et al.Identifying the source of subsynchronous control interaction via wide-area monitoring of sub/super-synchronous power flows[J]. IEEE Transactions on Power Delivery, 2020, 35(5): 2177-2185.
[13] 陈磊, 王文婕, 王茂海, 等. 利用暂态能量流的次同步强迫振荡扰动源定位及阻尼评估[J]. 电力系统自动化, 2016, 40(19): 1-8.
Chen Lei, Wang Wenjie, Wang Maohai, et al.Disturbance source location of subsynchronous forced oscillation and damping evaluation using transient energy flow[J]. Automation of Electric Power Systems, 2016, 40(19): 1-8.
[14] 姜涛, 高浛, 李筱静, 等. 基于小波耗散能量谱的电力系统强迫振荡源定位[J]. 电工技术学报, 2023, 38(7): 1737-1750.
Jiang Tao, Gao Han, Li Xiaojing, et al.Forced oscillation source location in power system using wavelet dissipation energy spectrum[J]. Transactions of China Electrotechnical Society, 2023, 38(7): 1737-1750.
[15] 陈剑, 杜文娟, 王海风. 基于对抗式迁移学习的含柔性高压直流输电的风电系统次同步振荡源定位[J]. 电工技术学报, 2021, 36(22): 4703-4715.
Chen Jian, Du Wenjuan, Wang Haifeng.Location method of subsynchronous oscillation source in wind power system with VSC-HVDC based on adversarial transfer learning[J]. Transactions of China Electrotechnical Society, 2021, 36(22): 4703-4715.
[16] Ping Zuowei, Li Xiuting, He Wei, et al.Sparse learning of network-reduced models for locating low frequency oscillations in power systems[J]. Applied Energy, 2020, 262: 114541.
[17] 谢小荣, 刘华坤, 贺静波, 等. 新能源发电并网系统的小信号阻抗/导纳网络建模方法[J]. 电力系统自动化, 2017, 41(12): 26-32.
Xie Xiaorong, Liu Huakun, He Jingbo, et al.Small-signal impedance/admittance network modeling for grid-connected renewable energy generation systems[J]. Automation of Electric Power Systems, 2017, 41(12): 26-32.
[18] Gong Hong, Yang Dongsheng, Wang Xiongfei.Impact analysis and mitigation of synchronization dynamics for DQ impedance measurement[J]. IEEE Transactions on Power Electronics, 2019, 34(9): 8797-8807.
[19] Maslennikov S, Litvinov E.ISO new England experience in locating the source of oscillations online[J]. IEEE Transactions on Power Systems, 2021, 36(1): 495-503.
[20] 周一辰, 孙佳辉, 王书祥, 等. 基于高维模型表达方法的新能源电力系统小干扰失稳风险评估[J]. 电力系统自动化, 2022, 46(14): 73-82.
Zhou Yichen, Sun Jiahui, Wang Shuxiang, et al.Risk assessment of small-signal instability for renewable power system based on high-dimensional model representation method[J]. Automation of Electric Power Systems, 2022, 46(14): 73-82.
[21] 徐衍会, 刘慧, 成蕴丹. 次同步振荡在交直流电网中传播的关键影响因素[J/OL]. 现代电力, 2023(4): 1-11.
Xu Yanhui, Liu Hui, Cheng Yundan.Key Influencing factors on propagation of sub-synchronous oscillations in AC and DC grids[J/OL]. Modern Electric Power, 2023(4): 1-11.
[22] 张涌新. 双馈风电并网系统宽频振荡机理及振荡源定位研究[D]. 北京: 华北电力大学, 2020.
[23] Ma Jian, Sun Zengqi.Mutual information is copula entropy[J]. Tsinghua Science & Technology, 2011, 16(1): 51-54.
[24] Ma Jian. Estimating transfer entropy via copula entropy[EB/OL].2019: arXiv: 1910.04375. https://arxiv.org/abs/1910.04375.pdf
[25] 唐锦, 张书怡, 吴秋伟, 等. 基于Copula函数与等概率逆变换的风电出力场景生成方法[J]. 电力工程技术, 2021, 40(6): 86-94.
Tang Jin, Zhang Shuyi, Wu Qiuwei, et al.Wind power output scenario generation method based on Copula function and equal probability inverse transformation[J]. Electric Power Engineering Technology, 2021, 40(6): 86-94.
[26] 李立, 张青蕾, 王康, 等. 风电并网系统次同步振荡传播路径频域定位方法[J]. 华北电力大学学报(自然科学版), 2023, 50(2): 54-62.
Li Li, Zhang Qinglei, Wang Kang, et al.Frequency domain location method of subsynchronous oscillation propagation path in wind power integrated system[J]. Journal of North China Electric Power University (Natural Science Edition), 2023, 50(2): 54-62.
[27] Granger C W J. Investigating causal relations by econometric models and cross-spectral methods[M]//Essays in Econometrics vol II: Collected Papers of Clive W. J. Granger. New York: Cambridge University Press, 2008: 31-47.
[28] 耿雪青, 佘青山, 张启忠, 等. 基于Copula的多变量运动想象脑电信号因果分析方法[J]. 航天医学与医学工程, 2018, 31(1): 49-56.
Geng Xueqing, She Qingshan, Zhang Qizhong, et al.Multivariate causality analysis method of motor imagery EEG signals based on copula[J]. Space Medicine & Medical Engineering, 2018, 31(1): 49-56.
[29] 姜涛, 刘博涵, 李雪, 等. 基于自适应投影多元经验模态分解的电力系统强迫振荡源定位[J]. 电工技术学报, 2023, 38(13): 3527-3538.
Jiang Tao, Liu Bohan, Li Xue, et al.Forced oscillation location in power systems using adaptive projection intrinsically transformed multiple empirical mode decomposition[J]. Transactions of China Electrotechnical Society, 2023, 38(13): 3527-3538.
[30] Ma Jian.Estimating Copula Entropy and Transfer Entropy[Source code]. https://github.com/majianthu/copent.2022.
[31] 王洪安. 上肢运动的肌间耦合分析方法研究[D]. 杭州: 杭州电子科技大学, 2021.
[32] 叶圣永, 王晓茹, 周曙, 等. 基于马尔可夫链蒙特卡罗方法的电力系统暂态稳定概率评估[J]. 电工技术学报, 2012, 27(6): 168-174.
Ye Shengyong, Wang Xiaoru, Zhou Shu, et al.Power system probabilistic transient stability assessment based on Markov chain Monte Carlo method[J]. Transactions of China Electrotechnical Society, 2012, 27(6): 168-174.
[33] Wibral M, Pampu N, Priesemann V, et al.Measuring information-transfer delays[J]. PLoS One, 2013, 8(2): e55809.
[34] 高本锋,董涵枭,卢亚军,等.直驱风电场并网对直流输电引起的火电机组轴系扭振影响机理分析[J/OL].电工技术学报:1-15[2023-10-13]. https://doi.org/10.19595/j.cnki.1000-6753.tces.230016.
Gao Benfeng, Dong Hanxiao, Lu Yajun, et al. Mechanism Analysis of the Influence of Direct Drive Wind Farm Integration on SSTI of Thermal Generator Caused by LCC-HVDC[J/OL]. Transactions of China Electrotechnical Society :1-15[2023-10-13]. https://doi.org/10.19595/j.cnki.1000-6753.tces.230016.
[35] 吴楠, 李尚盛, 查晓明. 改进的同步电机阻尼绕组电流观测器[J]. 电力系统保护与控制, 2015, 43(1): 67-72.
Wu Nan, Li Shangsheng, Zha Xiaoming.Improved synchronous generator damper current observer[J]. Power System Protection and Control, 2015, 43(1): 67-72.