Abstract:With the yearly growth of the stand-alone capacity of wind turbines, the negative impact of wind power fluctuations on the quality and frequency stability of the power grid is becoming increasingly severe. A novel control strategy for smoothing wind turbine output power is proposed using rotor kinetic energy. Specifically, the following work is included. (1) A novel smoothing reference power command is designed. (2) The influence of the key parameter in the rotor kinetic energy control framework and the integration period Δt on power tracking is analyzed. An optimization method for setting Δt is proposed. (3) The maximum power point tracking (MPPT) speed is set as the lower limit of the rotational speed, and the generator is allowed to output the reference power precisely through the speed closed-loop control structure. Firstly, the transfer function model of the wind turbine is established, and the steady-state operating point is determined according to the moving average filtering algorithm. The novel smooth reference power command is calculated, which decouples and adjusts the output power’s smoothness and average value by changing the values of parameters T and K. The larger the value of T, the more pronounced the power smoothing effect. The smaller the value of K, the lower the average output power. Then, through speed tracking simulation on the wind turbine, the speed tracking error caused by controller delay and other factors is recorded and analyzed to determine the optimal value of the integration period Δt. Finally, the precise response to power command is achieved through the speed closed-loop control structure, effectively avoiding the instability problem that may occur during the large-scale variable speed operation of the wind turbine. Compared with the traditional MPPT control strategy under 60s turbulent wind conditions in the simulation, the standard deviation of the output power using the proposed method is decreased by 9.97% when T=1, while the average value is only reduced by 1.2%. When T=3.5, the standard deviation is decreased by 27.29%, greatly improving waveform smoothness, and the average value is decreased by 5.2%. Since the MPPT speed is set as the lower speed limit, the wind turbine may cross the lower speed limit during operation and cause the power to fall. Therefore, reducing the value of K can reduce the average output power value, so the turbine operates in a high-speed interval. The turbine decelerating probability to the lower speed limit can be reduced. In the case of T=2.5 and K=0.85, the unit speed is always higher than the lower limit value, and the standard deviation of the output power is reduced by 32.19% compared with the MPPT strategy. The smoothness of output power is significantly improved, and the average value is only reduced to 90.76%. The simulation and experimental results show that after optimizing the integral period parameter, the speed closed-loop control structure can achieve the same effect as the power closed-loop control structure and accurately respond to the reference power command, which helps set the speed limit to prevent unit instability. The proposed power smoothing control strategy can effectively suppress wind power fluctuations while ensuring sufficient wind energy utilization efficiency. By setting the MPPT speed as the lower speed limit, the stable operation of the wind turbine can be ensured under turbulent wind conditions.
朱瑛, 李斌, 孔旻昊, 卫志农. 计及功率指令和积分周期优化的风电机组转子动能功率平滑控制[J]. 电工技术学报, 2025, 40(4): 1063-1077.
Zhu Ying, Li Bin, Kong Minhao, Wei Zhinong. Rotor Kinetic Energy Based Power Smoothing Control for Wind Turbines Considering Reference Power and Integration Period Optimization. Transactions of China Electrotechnical Society, 2025, 40(4): 1063-1077.
[1] 胡正阳, 高丙团, 张磊, 等. 风电机组双向支撑能力分析与自适应惯量控制策略[J]. 电工技术学报, 2023, 38(19): 5224-5240. Hu Zhengyang, Gao Bingtuan, Zhang Lei, et al.Bidirectional support capability analysis and adaptive inertial control strategy of wind turbine[J]. Transactions of China Electrotechnical Society, 2023, 38(19): 5224-5240. [2] 孔贺, 侯山, 赵弋菡, 等. 低电压穿越控制诱导的陆上风电场电压振荡的分岔分析及其判据研究[J/OL]. 中国电机工程学报: 1-20 [2024-04-28]. https://doi.org/10.13334/j.0258-8013.pcsee.230763. Kong He, Hou Shan, Zhao Gehan. Bifurcation analysis and criteria of voltage oscillation induced by low voltage ride through control in onshore wind farm[J/OL]. Proceedings of the CSEE: 1-20 [202404-28]. https://doi.org/10.13334/j.0258-8013.pcsee.23073. [3] 周伟波, 黄伟. 基于云边协同架构的海上风电场公共连接点电压控制方法[J]. 电气工程学报, 2023, 18(1): 169-180. Zhou Weibo, Huang Wei.Voltage control method for common connection point of offshore wind farm based on cloud edge collaborative architecture[J]. Journal of Electrical Engineering, 2023, 18(1): 169-180. [4] 颜湘武, 孙雪薇, 崔森, 等. 基于转子动能与超级电容器储能的双馈风电机组惯量和一次调频改进控制策略[J]. 电工技术学报, 2021, 36(增刊1): 179-190. Yan Xiangwu, Sun Xuewei, Cui Sen, et al.Improved control strategy for inertia and primary frequency regulation of doubly fed induction generator based on rotor kinetic energy and supercapacitor energy storage[J]. Transactions of China Electrotechnical Society, 2021, 36(S1): 179-190. [5] 张宇博, 杨松浩, 郝治国. 最大化电力系统频率最低点的并网风电机组频率支撑控制[J]. 电力系统自动化, 2024, 48(8): 141-151. Zhang Yubo, Yang Songhao, Hao Zhiguo.Frequency support control of grid-connected wind turbines to maximize frequency nadir of power systems[J]. Automation of Electric Power Systems, 2024, 48(8): 141-151. [6] 李京华, 王德林, 孙浩宁, 等. 双馈风电并网后系统的惯量特性研究及其最小惯量评估方法[J/OL]. 电气工程学报: 1-13 [2024-04-28]. http://kns.cnki.net/ kcms/detail/10.1289.TM.20230705.1705.002.html. Li Jinghua, Wang Delin, Sun Haoning, et al. Research on inertia characteristics and minimum inertia evaluation method of doubly-fed wind power system after grid connection[J/OL]. Journal of Electrical Engineering: 1-13[2024-04-28]. http://kns.cnki.net/kcms/ detail/10.1289.TM.20230705.1705.002.html. [7] 朱瑛, 高云波, 臧海祥, 等. 风电机组输出功率平滑技术综述[J]. 电力系统自动化, 2018, 42(18): 182-191. Zhu Ying, Gao Yunbo, Zang Haixiang, et al.Review of output power smoothing technologies for wind turbine[J]. Automation of Electric Power Systems, 2018, 42(18): 182-191. [8] 林莉, 林雨露, 谭惠丹, 等. 计及SOC自恢复的混合储能平抑风电功率波动控制[J]. 电工技术学报, 2024, 39(3): 658-671. Lin Li, Lin Yulu, Tan Huidan, et al.Hybrid energy storage control with SOC self-recovery to smooth out wind power fluctuations[J]. Transactions of China Electrotechnical Society, 2024, 39(3): 658-671. [9] 赵靖英, 乔珩埔, 姚帅亮, 等. 考虑储能SOC自恢复的风电波动平抑混合储能容量配置策略[J]. 电工技术学报, 2024, 39(16): 5206-5219. Zhao Jingying, Qiao Hengpu, Yao Shuailiang, et al.Hybrid energy storage system capacity configuration strategy for stabilizing wind power fluctuation considering SOC self-recovery[J]. Transactions of China Electrotechnical Society, 2024, 39(16): 5206-5219. [10] 周皓, 李军徽, 葛长兴, 等. 改善风电并网电能质量的飞轮储能系统能量管理系统设计[J]. 太阳能学报, 2021, 42(3): 105-113. Zhou Hao, Li Junhui, Ge Changxing, et al.Research on improving power quality of wind power system based on energy management system of flywheel energy storage system[J]. Acta Energiae Solaris Sinica, 2021, 42(3): 105-113. [11] 李忠瑞, 聂子玲, 艾胜, 等. 一种基于非线性扰动观测器的飞轮储能系统优化充电控制策略[J]. 电工技术学报, 2023, 38(6): 1506-1518. Li Zhongrui, Nie Ziling, Ai Sheng, et al.An optimized charging control strategy for flywheel energy storage system based on nonlinear disturbance observer[J]. Transactions of China Electrotechnical Society, 2023, 38(6): 1506-1518. [12] 汤雪松, 殷明慧, 李冬运, 等. 变速与变桨协调的风电机组平滑功率控制[J]. 电力系统自动化, 2019, 43(2): 112-120. Tang Xuesong, Yin Minghui, Li Dongyun, et al.Power smoothing control of wind turbine generator via coordinated rotor speed and pitch angle regulation[J]. Automation of Electric Power Systems, 2019, 43(2): 112-120. [13] Van T L, Nguyen T H, Lee D C.Advanced pitch angle control based on fuzzy logic for variable-speed wind turbine systems[J]. IEEE Transactions on Energy Conversion, 2015, 30(2): 578-587. [14] Senjyu T, Sakamoto R, Urasaki N, et al.Output power leveling of wind turbine Generator for all operating regions by pitch angle control[J]. IEEE Transactions on Energy Conversion, 2006, 21(2): 467-475. [15] Luo Changling, Banakar H, Shen Baike, et al.Strategies to smooth wind power fluctuations of wind turbine generator[J]. IEEE Transactions on Energy Conversion, 2007, 22(2): 341-349. [16] Jia Feng, Cai Xu, Li Zheng.Fluctuating characteristic and power smoothing strategies of WECS[J]. IET Generation, Transmission & Distribution, 2018, 12(20): 4568-4576. [17] Qin Zian, Blaabjerg F, Loh P C.A rotating speed controller design method for power leveling by means of inertia energy in wind power systems[J]. IEEE Transactions on Energy Conversion, 2015, 30(3): 1052-1060. [18] 陈载宇, 沈春, 殷明慧, 等. 面向AGC的变速变桨风电机组有功功率控制策略[J]. 电力工程技术, 2017, 36(1): 9-14. Chen Zaiyu, Shen Chun, Yin Minghui, et al.Review of active power control strategy for variable-speed variable-pitch wind turbine participating in AGC[J]. Electric Power Engineering Technology, 2017, 36(1): 9-14. [19] 周银, 林桦. 平滑永磁同步风电系统功率波动的改进最佳转矩控制策略[J]. 电力系统自动化, 2013, 37(9): 13-17, 73. Zhou Yin, Lin Hua.Improved optimal torque control strategy for smoothing power fluctuations of permanent magnet synchronous generator for wind turbine[J]. Automation of Electric Power Systems, 2013, 37(9): 13-17, 73. [20] Lü Xue, Zhao Jian, Jia Youwei, et al.Coordinated control strategies of PMSG-based wind turbine for smoothing power fluctuations[J]. IEEE Transactions on Power Systems, 2019, 34(1): 391-401. [21] Zhao Xianxian, Yan Zuanhong, Xue Ying, et al.Wind power smoothing by controlling the inertial energy of turbines with optimized energy yield[J]. IEEE Access, 2017, 5: 23374-23382. [22] 王海旗, 晋涛, 刘星廷, 等. 基于转子动能控制的风电机组功率平滑控制结构及优化策略研究[J]. 太阳能学报, 2022, 43(9): 251-257. Wang Haiqi, Jin Tao, Liu Xingting, et al.Research on wind turbine power smooth control structure and optimization strategy based on rotor kinetic energy control[J]. Acta Energiae Solaris Sinica, 2022, 43(9): 251-257. [23] Liao Kai, Lu Dingwen, Wang Min, et al.A low-pass virtual filter for output power smoothing of wind energy conversion systems[J]. IEEE Transactions on Industrial Electronics, 2022, 69(12): 12874-12885. [24] 殷明慧, 顾伟, 陈载宇, 等. 面向风电机组有功功率控制的风轮变速运行模式比较研究[J]. 中国电机工程学报, 2022, 42(12): 4419-4430. Yin Minghui, Gu Wei, Chen Zaiyu, et al.Comparative study of rotor speed variation modes for active power control of wind turbine generators[J]. Proceedings of the CSEE, 2022, 42(12): 4419-4430. [25] Lin Jin, Sun Yuanzhang, Song Yonghua, et al.Wind power fluctuation smoothing controller based on risk assessment of grid frequency deviation in an isolated system[J]. IEEE Transactions on Sustainable Energy, 2013, 4(2): 379-392.