数据驱动的风光场站次同步振荡多机协同阻尼控制方法

doi:10.19595/j.cnki.1000-6753.tces.231143

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Abstract With the rapid growth of photovoltaic and wind power’s access scale in the power grid, the problem of sub-synchronous oscillation (SSO) in the power system has become increasingly prominent. At present, the design scheme of new energy sub-synchronous damping control (SSDC) is mainly based on the model-driven control method, which relies on the accurate system state equation. However, the power system has time-varying and nonlinear characteristics, and the existing SSDC controller for new energy has limited applications, making it difficult to adapt to complex and changeable operating conditions. Therefore, finding a new strategy to break the barriers in damping control is urgent. At the same time, the existing literature has not explored the multi-machine equivalent model with multiple new energy types.
According to previous engineering experience and analysis, the input and output signals of the multi-machine cooperative damping controller are selected. The feedback signal is selected as the grid-connected voltage of the new energy station, and the input position is selected as the inner d-axis of the inverter of the photovoltaic and double-fed wind farms. Then, for a new energy station containing multiple photovoltaic power stations and multiple wind turbines, in the process of designing the SSDC controller, it is similarly equivalent to a multi-input single-output system, and a model-free adaptive control (MFAC) algorithm for multi-machine coordination is designed. The parameters of the simulation system and the controller are designed, and the controller parameters are optimized by the simplex method. Finally, the impedance frequency scan analysis and simulation are carried out in the IEEE 39-node system connected to the new energy station through serial compensation, and the effectiveness of the multi-machine cooperative damping strategy is verified.
The following conclusions can be drawn. (1) Impedance frequency analysis shows that the damping control method can effectively reshape the impedance of the new energy station system and significantly improve the positive sequence equivalent resistance of the system in the range of sub-synchronous frequency, reflecting good SSO suppression potential. (2) The numerical example shows that the damping control method has a significant effect on the cooperative control of the equivalent four-machine system of wind power and photovoltaic. A complete control process only requires 24 addition/subtraction calculations and 28 multiplication/division calculations, reducing calculation costs. (3) Considering the input time of the damping controller, the scale of the new energy station, the proportion of wind power out put to solar power output, and the influence of large and small disturbances of the system (changes in wind speed or radiation intensity, the cutting load of the cutting machine), the controller can effectively suppress the sub-synchronous oscillation and is insensitive to the oscillation frequency deviation. In conclusion, the multi-machine cooperative model-free sub-synchronous damping control strategy is adaptable to new energy stations containing multi-PV and multi-DFIG.

Key words： Model-free adaptive control damping control sub-synchronous oscillation new energy station cooperative control data-driven

Received: 16 July 2023

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	Zhen Yongzan
	Di Yirong
	Hu Yongqiang
	Gao Bengfeng

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Zhen Yongzan,Di Yirong,Hu Yongqiang等. Data-Driven Multi-Machine Cooperative Damping Control for Wind and Photovoltaic Plants Restraining Sub-Synchronous Oscillation[J]. Transactions of China Electrotechnical Society, 2024, 39(18): 5855-5867.

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[1] 国家能源局. 国家能源局2023年一季度新闻发布会文字实录[EB/OL]. [2023-02-13]. http://www.nea. gov.cn/2023-02/13/c_1310697149.htm.
[2] 王伟胜, 李光辉, 何国庆, 等. 新能源并网系统宽频振荡分析与抑制[M]. 北京: 中国电力出版社, 2022.
[3] IEEE Power & Energy Society. Wind energy systems sub-synchronous oscillations: events and modeling (TR80)[R]. Piscataway, NJ: IEEE PES, 2020.
[4] Narendra K, Fedirchuk D, Midence R.New microprocessor based relay to monitor and protect power systems against sub-harmonics[C]//2011 IEEE Electrical Power and Energy Conference, Winnipeg, 2011: 438-443.
[5] XIE X R, ZHANG X, LIU H K, et al.Characteristic analysis of subsynchronous resonance in practical wind farms connected to series-compensated trans- missions[J]. IEEE Transactions on Energy Conversion, 2017, 32(3): 1117-1126.
[6] 赵书强, 李忍, 高本锋, 等. 光伏并入弱交流电网次同步振荡机理与特性分析[J]. 中国电机工程学报, 2018, 38(24): 7215-7225, 7448.
Zhao Shuqiang, Li Ren, Gao Benfeng, et al.Analysis of mechanism and characteristics in sub synchronous oscillation between PV and weak AC networks[J]. Proceedings of the CSEE, 2018, 38(24): 7215-7225, 7448.
[7] 陈建, 任永峰, 孟庆天, 等. 含UDE附加阻尼支路的构网型直驱永磁同步风电机组次同步振荡抑制策略[J]. 电工技术学报, 2024, 39(7): 1985-2000.
Chen Jian, Ren Yongfeng, Meng Qingtian, et al.Sub-synchronous oscillation suppression strategy for grid-forming direct-drive permanent magnet syn- chronous generator with uncertainty and disturbance estimator supplementary damping branch[J]. Transa- ctions of China Electrotechnical Society, 2024, 39(7): 1985-2000.
[8] 贾祺, 严干贵, 李泳霖, 等. 多光伏发电单元并联接入弱交流系统的稳定性分析[J]. 电力系统自动化, 2018, 42(3): 14-20.
Jia Qi, YanGangui, Li Yonglin, et al. Stability analysis of multiple paralleled photovoltaic power generation units connected to weak AC system[J]. Automation of Electric Power Systems, 2018, 42(3): 14-20.
[9] 刘佳宁, 于淼, 夏杨红, 等. 受弱电网影响光伏并网系统不同频段稳定性分析[J]. 电网技术, 2020, 44(1): 86-95.
Liu Jianing, Yu Miao, Xia Yanghong, et al.Separated frequency stability analysis of grid-connected PV system affected by weak grid[J]. Power System Technology, 2020, 44(1): 86-95.
[10] Fan Lingling, Yin Haiping, Miao Zhixin.On active/ reactive power modulation of DFIG-based wind generation for interarea oscillation damping[J]. IEEE Transactions on Energy Conversion, 2011, 26(2): 513-521.
[11] 高本锋, 王义, 范辉, 等. 基于阻尼路径的新能源经LCC-HVDC送出系统次同步交互作用分析方法[J]. 电工技术学报, 2023, 38(20): 5572-5589.
Gao Benfeng, Wang Yi, Fan Hui, et al.A sub- synchronous interaction analysis method of renewable energy generations integrated with LCC-HVDC system based on damping path[J]. Transactions of China Electrotechnical Society, 2023, 38(20): 5572-5589.
[12] 汪洋. 大型光伏并网系统的复杂振荡问题研究[D]. 北京: 华北电力大学, 2018.
[13] Yao Jun, Wang Xuewei, Li Jiawei, et al.Sub- synchronous resonance damping control for series- compensated DFIG-based wind farm with improved particle swarm optimization algorithm[J]. IEEE Transactions on Energy Conversion, 2019, 34(2): 849-859.
[14] Zhang Xu, Xie Xiaorong, Liu Hui, et al.Robust subsynchronous damping control to stabilise SSR in series-compensated wind power systems[J]. IET Generation, Transmission & Distribution, 2019, 13(3): 337-344.
[15] 高本锋, 张学伟, 李忍. 大规模风电送出系统的次同步振荡问题研究综述[J]. 电气工程学报, 2015, 10(7): 1-10.
Gao Benfeng, Zhang Xuewei, Li Ren.Studies of sub-synchronous oscillation in system with large- scale wind power transmission[J]. Journal of Elec- trical Engineering, 2015, 10(7): 1-10.
[16] Yan Shuxuan, Zhou Yunpeng, Zhu Jianhang, et al.An improved SSR damping strategy based on SSDC in photovoltaic grid-connected system[C]//2022 IEEE International Power Electronics and Application Conference and Exposition, Guangzhou, 2022: 693-697.
[17] 姜齐荣, 王玉芝. 电力电子设备高占比电力系统电磁振荡分析与抑制综述[J]. 中国电机工程学报, 2020, 40(22): 7185-7201.
Jiang Qirong, Wang Yuzhi.Overview of the analysis and mitigation methods of electromagnetic oscillations in power systems with high proportion of power electronic equipment[J]. Proceedings of the CSEE, 2020, 40(22): 7185-7200.
[18] 高本锋, 姚磊. 基于改进自抗扰控制的抑制光火打捆经直流送出系统的次同步振荡策略[J]. 电网技术, 2018, 42(2): 533-540.
Gao Benfeng, Yao Lei.Sub-Synchronous oscillation suppression for photovoltaic-thermal-bundled power system based on improved active disturbance rejection control[J]. Power System Technology, 2018, 42(2): 533-540.
[19] 高本锋, 姚磊. 模糊自抗扰附加阻尼控制抑制光火打捆经串补送出的次同步振荡[J]. 电力自动化设备, 2018, 38(7): 121-127.
Gao Benfeng, Yao Lei.Supplementary damping control of SSO based on fuzzy active disturbance rejection control for photovoltaic-thermal-bundled system transmitted by series compensation[J]. Electric Power Automation Equipment, 2018, 38(7): 121-127.
[20] Azghandi M A, Barakati S M.Virtual RL damping and harmonic suppression for current-source inverter- based photovoltaic systems[C]//2019 10th Inter- national Power Electronics, Drive Systems and Technologies Conference, Shiraz, Iran, 2019: 572-576.
[21] 孙焜, 姚伟, 周毅, 等. 基于SISO序阻抗的直驱风场经柔直输电系统中频振荡机理分析及抑制[J]. 中国电机工程学报, 2023, 43(2): 442-454.
Sun Kun, Yao Wei, Zhou Yi, et al.Mechanism analysis and suppression of medium-frequency oscillation based on the SISO impedance in a PMSG- based wind farm when connected to a VSC-HVDC[J]. Proceedings of the CSEE, 2023, 43(2): 442-454.
[22] 李浩志, 谢小荣, 刘芮彤, 等. 新能源经柔直送出系统的次同步振荡分析与抑制[J]. 中国电机工程学报, 2024, 44(6): 2945-2954.
Li Haozhi, Xie Xiaorong, Liu Ruitong, et al.Analysis and mitigation of the subsynchronous oscillation in renewable energy system connected to the MMC- HVDC[J]. Proceedings of the CSEE, 2024, 44(6): 2945-2954.
[23] 吴熙, 徐珊珊, 冯双, 等. 基于改进自适应陷波的双馈风电场时变次同步振荡抑制策略[J]. 中国电机工程学报, 2024, 44(5): 1836-1849.
Wu Xi, Xu Shanshan, Feng Shuang, et al.Time- varying subsynchronous oscillation mitigation strategy for DFIG wind farms based on improved adaptive notch filter[J]. Proceedings of the CSEE, 2024, 44(5): 1836-1849.
[24] Li Penghan, Xiong Linyun, Wu Fei, et al.Sliding mode controller based on feedback linearization for damping of sub-synchronous control interaction in DFIG-based wind power plants[J]. International Journal of Electrical Power & Energy Systems, 2019, 107(5): 239-250.
[25] Karunanayake C, Ravishankar J, Dong Zhaoyang.Nonlinear SSR damping controller for DFIG based wind generators interfaced to series compensated transmission systems[J]. IEEE Transactions on Power Systems, 2020, 35(2): 1156-1165.
[26] 王智伟, 李鹏瀚, 刘鑫, 等. 基于分数阶滑模控制的双馈风电系统次同步振荡抑制方法[J]. 中国电机工程学报, 2023, 43(19):7519-7530.
Wang Zhiwei, Li Penghan, Liu Xin, et al.Suppression method of subsynchronous oscillation in DFIG-based wind power system based on fractional-order sliding mode control[J]. Proceedings of the CSEE, 2023, 43(19): 7519-7530.
[27] 冯双, 崔昊, 陈佳宁, 等. 人工智能在电力系统宽频振荡中的应用与挑战[J]. 中国电机工程学报, 2021, 41(23): 7889-7905.
Feng Shuang, Cui Hao, Chen Jianing, et al.Appli- cations and challenges of artificial intelligence in power system wide-band oscillations[J]. Proceedings of the CSEE, 2021, 41(23): 7889-7905.
[28] 陈柔伊, 张尧, 钟庆, 等. 抑制区间振荡的自适应模糊广域阻尼控制设计[J]. 中国电机工程学报, 2009, 29(31): 14-20.
Chen Rouyi, Zhang Yao, Zhong Qing, et al.Self-adaptive fuzzy wide-area control design for damping inter-area oscillations[J]. Proceedings of the CSEE, 2009, 29(31): 14-20.
[29] 余希瑞, 周林, 郭珂, 等. 多模型自适应控制应用于大型光伏电站阻尼区间振荡[J]. 中国电机工程学报, 2017, 37(14): 4036-4043, 4282.
Yu Xirui, Zhou Lin, Guo Ke, et al.Application of multiple-model adaptive control for damping inter- area oscillations by large-scale photovoltaic plant[J]. Proceedings of the CSEE, 2017, 37(14): 4036-4043, 4282.
[30] 孙东阳, 孟繁易, 王南, 等. 基于反步自适应准谐振控制的双馈风机次同步振荡抑制策略[J]. 电工技术学报, 2023, 38(9): 2375-2390, 2434.
Sun Dongyang, Meng Fanyi, Wang Nan, et al.DFIG sub-synchronous oscillation suppression strategy based on backstepping adaptive quasi-resonant control[J]. Transactions of China Electrotechnical Society, 2023, 38(9): 2375-2390, 2434.
[31] 苗硕, 李奇南, 查鲲鹏, 等. 基于加窗FFT的风电场自适应振荡抑制策略[J]. 中国电力, 2022, 55(10): 112-123.
Miao Shuo, Li Qinan, Zha Kunpeng, et al.Adaptive oscillation suppression strategy for wind farms based on windowed FFT[J]. Electric Power, 2022, 55(10): 112-123.
[32] 侯忠生, 金尚泰. 无模型自适应控制——理论与应用[M]. 北京: 科学出版社, 2013.
[33] 吴熙, 王梦婷, 施星宇, 等. 基于无模型自适应控制的双馈风机次同步振荡附加阻尼控制方法[J]. 中国电机工程学报, 2022, 42(10): 3601-3614.
Wu Xi, Wang Mengting, Shi Xingyu, et al.SSO supplementary damping control method for DFIG based on model-free adaptive control[J]. Proceedings of the CSEE, 2022, 42(10): 3601-3614.
[34] 杨朋威, 任正, 王新宇, 等. 基于MFAC附加阻尼控制器的次同步振荡抑制方法[J]. 电力系统及其自动化学报, 2023, 35(9): 68-78.
Yang Pengwei, Ren Zheng, Wangxinyu, et al. Sub-synchronous oscillation suppression method based on MFAC sub-synchronous damping con- troller[J]. Proceedings of the CSU-EPSA, 2023, 35(9): 68-78.
[35] 刘国海, 陈仁杰, 张多, 等. 两电机调速系统的神经网络逆无模型自适应鲁棒解耦控制[J]. 中国电机工程学报, 2019, 39(3): 868-874, 965.
Liu Guohai, Chen Renjie, Zhang Duo, et al.Model-free adaptive robust control for two motor drive system based on neural network inversion[J]. Proceedings of the CSEE, 2019, 39(3): 868-874, 965.
[36] 陈宗遥, 卜旭辉, 郭金丽. 基于神经网络的数据驱动互联电力系统负荷频率控制[J]. 电工技术学报, 2022, 37(21): 5451-5461.
Chen Zongyao, Bu Xuhui, Guo Jinli.Neural network based data-driven load frequency control for interconnected power systems[J]. Transactions of China Electrotechnical Society, 2022, 37(21): 5451-5461.
[37] 曹荣敏, 郑鑫鑫, 侯忠生. 基于改进多入多出无模型自适应控制的二维直线电机迭代学习控制[J]. 电工技术学报, 2021, 36(19): 4025-4034.
Cao Rongmin, Zheng Xinxin, Hou Zhongsheng.An iterative learning control based on improved multiple input and multiple output model free adaptive control for two-dimensional linear motors[J]. Transactions of China Electrotechnical Society, 2021, 36(19): 4025-4034.
[38] 邵冰冰, 赵峥, 肖琪, 等. 多直驱风机经柔直并网系统相近次同步振荡模式参与因子的弱鲁棒性分析[J] . 电工技术学报, 2023, 38(3): 754-769.
Shao Bingbing, Zhao Zheng, Xiao Qi, et al.Weak robustness analysis of close subsynchronous oscillation modes’ participation factors in multiple direct-drive wind turbines with the VSC-HVDC system[J]. Transactions of China Electrotechnical Society, 2023, 38(3): 754-769.
[39] 宫泽旭, 艾力西尔· 亚尔买买提, 辛焕海, 等. 新能源电力系统并网设备小扰动稳定分析(一): 机理模型与稳定判据适用性[J]. 中国电机工程学报, 2022, 42(12): 4405-4419.
Gong Zexü, Yaermaimaiti Ailixier, Xin Huanhai, et al.Small signal stability analysis of equipment in renewable energy power system (part I): mechanism model and adaptation of stability criterion[J]. Proceedings of the CSEE, 2022, 42(12): 4405-4419.
[40] 高本锋, 邓鹏程, 梁纪峰, 等. 光伏电站与弱交流电网间次同步交互作用路径及阻尼特性分析[J]. 电工技术学报, 2023, 38(24): 6679-6694.
Gao Benfeng, Deng Pengcheng, Liang Jifeng, et al.Analysis of path and damping characteristics of subsynchronous interaction between photovoltaic plant and weak AC grid[J]. Transactions of China Electrotechnical Society, 2023, 38(24): 6679-6694.
[41] 吴天昊, 谢小荣, 姜齐荣. 风电系统次同步等幅振荡的机理与特性分析[J]. 中国电机工程学报, 2023, 43(7): 2689-2699.
Wu Tianhao, Xie Xiaorong, Jiang Qirong.On subsynchronous sustained oscillation issues of wind power systems[J]. Proceedings of the CSEE, 2023, 43(7): 2689-2699.
[42] 柴天佑, 岳恒. 自适应控制[M]. 北京: 清华大学出版社, 2016.
[43] 符玲, 韩文朕, 麦瑞坤, 等. 基于频域动态模型的同步相量测量算法[J]. 中国电机工程学报, 2015, 35(6): 1371-1378.
Fu Ling, Han Wenzhen, Mai Ruikun, et al.Dynamic phasor estimator based on frequency-domain model[J]. Proceedings of the CSEE, 2015, 35(6): 1371-1378.
[44] 韩璞. 现代工程控制论[M]. 北京: 中国电力出版社, 2017.
[45] 冯增喜, 任庆昌, 彭彦平, 等. 基于单纯形法的MFAC参数寻优[J]. 控制工程, 2016, 23(3): 405-410.
Feng Zengxi, Ren Qingchang, Peng Yanping, et al.Optimizing the parameters of MFAC based on the simplex method[J]. Control Engineering of China, 2016, 23(3): 405-410.
[46] 赵成勇, 刘娟. Prony算法在电力系统暂态信号分析中的应用[J]. 电力系统及其自动化学报, 2008, 20(2): 60-64.
Zhao Chengyong, Liu Juan.Analysis of power system transient signal based on Prony algorithm[J]. Proceedings of the CSU-EPSA, 2008, 20(2): 60-64.