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

doi:10.19595/j.cnki.1000-6753.tces.201500

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Abstract Wind farms connected to AC systems via voltage source converter based high voltage direct current transmission (VSC-HVDC), which will generate subsynchronous oscillations (SSO). It is an urgent problem to locate the source of SSO in wind farms and take targeted suppression measures in time. This paper establishes the linearization model of the power system of wind farms connected to the grid via VSC-HVDC, analyzes the mechanism of wind farms inducing SSO due to interaction, and proposes a wind farm SSO source location method based on adversarial transfer learning. This method reduces the domain difference between the simulation system and the actual system by learning from the oscillation features of the two systems, and realizes that the location model established by the simulation system offline can be transferred to the actual system, thus to locate the SSO source in the wind farms. Through designing a power system case where multiple wind farms are connected to the grid via VSC-HVDC, it is verified and analyzed that the proposed method has high locating accuracy in different systems. This has important reference value for the power grid dispatching operation based on the wide-area measurement system to identify the source of oscillation or to provide an oscillation suppression strategy.

Key words： Adversarial transfer learning subsynchronous oscillation (SSO) voltage source converter based high voltage direct current transmission(VSC-HVDC) oscillation source location

Received: 14 November 2020

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TM712

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	Chen Jian
	Du Wenjuan
	Wang Haifeng

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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.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.201500 OR https://dgjsxb.ces-transaction.com/EN/Y2021/V36/I22/4703

[1] 付强, 杜文娟, 王海风. 柔性直流输电控制与交流系统次同步交互机理研究[J]. 中国电机工程学报, 2018, 38(13): 3717-3726, 4013.
Fu Qiang, Du Wenjuan, Wang Haifeng.The mechanism of sub-synchronous interactions between converter control of VSC HVDC and power systems[J]. Proceedings of the CSEE, 2018, 38(13): 3717-3726, 4013.
[2] 王一凡, 赵成勇, 郭春义. 双馈风电场孤岛经模块化多电平换流器直流输电并网系统小信号稳定性分析与振荡抑制方法[J]. 电工技术学报, 2019, 34(10): 2116-2129.
Wang Yifan, Zhao Chenyong, Guo Chunyi.Small signal stability and oscillation suppression method for islanded double fed induction generator-based wind farm integrated by modular multilevel converter based HVDC system[J]. Transactions of China Electrotechnical Society, 2019, 34(10): 2116-2129.
[3] 杨悦, 李国庆. 基于VSC-HVDC的海上风电小干扰稳定控制[J]. 电工技术学报, 2016, 31(13): 101-110.
Yang Yue, Li Guoqing.The small signal stability control of offshore wind farm based on VSC-HVDC[J]. Transactions of China Electrotechnical Society, 2016, 31(13): 101-110.
[4] 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): 4720-4731.
Ma Ningning, Xie Xiaorong, He Jingbo, et al.Review and discussion of wide-band oscillation in renewable and power electronics highly integrated power systems[J]. Proceedings of the CSEE, 2020, 40(15): 4720-4731.
[5] Strachan W, Jovcic D.Stability of a variable-speed permanent magnet wind generator with weak AC grids[J]. IEEE Transactions on Power Delivery, 2010, 25(4): 2779-2788.
[6] Bayo-Salas A, Beerten J, Rimez J, et al.Analysis of control interactions in multi-infeed VSC HVDC connections[J]. IET Generation Transmission & Distribution, 2016, 10(9): 1336-1344.
[7] 邵冰冰, 赵书强, 高本锋, 等. 连接弱交流电网的VSC-HVDC失稳机理及判据研究[J]. 电工技术学报, 2019, 34(18): 3884-3896.
Shao Bingbing, Zhao Shuqiang, Gao Benfeng, et al.Instability mechanism and criterion analysis of VSC-HVDC connected to the weak AC power grid[J]. Transactions of China Electrotechnical Society, 2019, 34(18): 3884-3896.
[8] 陈磊, 王文捷, 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.
[9] 许璞轩. 风电汇集区域次同步频率分量的传播路径与扰动源定位研究[D]. 北京: 华北电力大学, 2018.
[10] 李文锋, 郭剑波, 李莹, 等. 基于WAMS的电力系统功率振荡分析与振荡源定位(1)割集能量法[J].中国电机工程学报, 2013, 33(25): 41-46.
Li Wenfeng, Guo Jianbo, Li Ying, et al.Power system oscillation analysis and oscillation source location based on WAMS: part 1 method of cutset energy[J]. Proceedings of the CSEE, 2013, 33(25): 41-46.
[11] 陈厚合, 王长江, 姜涛, 等. 基于端口能量的含VSC-HVDC的交直流混合系统暂态稳定评估[J]. 电工技术学报, 2018, 33(3): 498-511.
Chen Houhe, Wang Changjiang, Jiang Tao, et al.Transient stability assessment in hybrid AC/DC systems with VSC-HVDC via port energy[J]. Transactions of China Electrotechnical Society, 2018, 33(3): 498-511.
[12] 马宁宁,谢小荣, 亢朋朋, 等. 高比例风电并网系统次同步振荡的广域监测与分析[J]. 中国电机工程学报, 2021,41(1): 65-74.
Ma Ningning, Xie Xiaorong, Kang Pengpeng, et al.Wide-area monitoring and analysis of subsynchronous oscillation in power systems with high-penetration of wind power[J]. Proceedings of the CSEE, 2021, 41(1): 65-74.
[13] Xie Xiaorong, Zhan Ying, Jan S, 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.
[14] Banna H, Solanki S, Solanki J.Data-driven disturbance source identification for power system oscillations using credibility search ensemble learning[J]. IET Smart Grid, 2019, 2(2): 293-300.
[15] 冯双, 陈佳宁, 汤奕, 等. 基于SPWVD图像和深度迁移学习的强迫振荡源定位方法[J]. 电力系统自动化, 2020, 44(17): 78-91.
Feng Shuang, Chen Jianing, Tang Yi, et al.Location method of forced oscillation source based on SPWVD image and deep transfer learning[J]. Automation of Electric Power systems, 2020, 44(17): 78-91.
[16] 陈剑, 杜文娟, 王海风. 采用深度迁移学习定位含直驱风机次同步振荡源机组的方法[J]. 电工技术学报: 2021, 36(1): 179-190.
Chen Jian, Du Wenjuan, Wang Haifeng.A method of locating the power system subsynchronous oscillation source unit with grid-connected PMSG using deep transfer learning[J]. Transactions of China Electrote-chnical Society, 2021, 36(1): 179-190.
[17] Yang Qiang, Zhang Yu, Dai Wenyuan, et al.Transfer learning[M]. Cambridge: United Kingdom:Cambridge University Press, 2020.
[18] Ganin Y, Lempitsky V.Unsupervised domain adaptation by backpropagation[C]//International Conference on Machine Learning, Lille, France, 2015, 37: 1180-1189.
[19] Ganin Y, Ajakan H, Larochelle H, et al.Domain-adversarial training of neural networks[J]. Journal of Machine Learning Research, 2016, 17(1): 1-35.
[20] 甄自竞, 杜文娟, 王海风. 近似强模式谐振下高压直流输电系统引起的次同步振荡仿真研究[J]. 中国电机工程学报, 2019, 39(7): 1976-1985.
Zhen Zijing, Du Wenjuan, Wang Haifeng.The simulation study on SSOs caused by the HVDC under the condition of near strong modal resonance[J]. Proceedings of the CSEE, 2019, 39(7): 1976-1985.
[21] Du Wenjuan, Wang Yang, Wang Haifeng.Concept of modal repulsion in examining the sub-synchronous oscillations in power system[J]. IEEE Transaction on Power Systems, 2018, 33(4): 4614-4624.
[22] Du Wenjuan, Dong Wenkai, Wang Haifeng, et al.Dynamic aggregation of same wind turbine generators in parallel connection for studying oscillation stability of a wind farm[J]. IEEE Transactions on Power Systems, 2019, 34(6): 4694-4705.
[23] Li Weixing, Chao Pupu, Liang Xiaodong, et al.A practical equivalent method for DFIG wind farms[J]. IEEE Transactions on Sustainable Energy, 2018, 9(2): 610-620.
[24] Brink H, Richards J, Fetherolf M.Real-world machine learning: model evaluation and optimization[M]. Greenwich: Manning Publications, 2016.