基于可用调频能量的风电机组综合虚拟惯性控制参数整定

doi:10.19595/j.cnki.1000-6753.tces.240400

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (2133 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract The additional integrated virtual inertia control of wind turbine is an important measure to improve the frequency stability of new type power system. It is of great significance to evaluate the frequency regulation capability of wind turbine under this control effectively and make full use of the frequency regulation capability by setting control parameters reasonably, hence, an integrated virtual inertia control parameter setting method for wind turbine based on available frequency regulation energy is proposed.
Firstly, considering the mechanical energy loss, a mathematical model describing the relationship between available rotor kinetic energy and rotor speed is constructed from the perspective of energy, and the effect of wind speed on available rotor kinetic energy is discovered. Secondly, the available frequency regulation energy is converted into available frequency regulation power, so that the relationship between the available frequency regulation power and wind speed can be described intuitively. On this basis, in order to make full use of the available frequency regulation power, the relational expression between the frequency regulation power and the control parameters is established. Considering the frequency regulation requirements in different scenarios, the fuzzy control rules are designed, and the control parameter setting values are obtained by using the fuzzy logic control method when the comprehensive effect of the system frequency change rate and the lowest frequency is optimal. Finally, the proposed method is applied to a 3-machines 9-nodes system, and the effectiveness of the proposed method is verified by simulation.
It is found that the maximum available frequency regulation power of wind turbine increases with the increase of wind speed. Under rated wind speed, the maximum available frequency regulation power of 2 MW wind turbine is 3% of rated power. In the simulation example, the proposed parameter setting method is compared with those without additional control, constant coefficient control and the parameter setting method of energy distribution mechanism of synchronous machine. The simulation results show that, at low wind speed, the method that does not consider the available frequency regulation energy exceeds the rotor speed limit corresponding to the maximum available frequency regulation energy due to the large parameter setting, and not only the frequency regulation effect becomes worse, moreover, the secondary frequency drop is aggravated due to excessive release of kinetic energy of rotor. At high wind speed, the parameter setting is too small, so the kinetic energy of the rotor is not fully utilized. When the available frequency regulation energy is considered, the rotor kinetic energy can be utilized to the maximum extent within the rotor speed limit of the wind turbine, and the frequency regulation effect is better. At the same time, compared with the energy distribution mechanism of synchronous machine, the proposed parameter setting method based on fuzzy control can consider the adjustment requirements of the frequency change rate and the lowest frequency under different scenarios, and determine the priority of frequency regulation, so as to optimize the comprehensive control effect of the system.
The following conclusions can be obtained through the analysis and verification: (1) The mathematical model of available frequency regulation power of wind turbine considering mechanical energy loss can directly describe the relationship between available frequency regulation power of wind turbine and wind speed. (2) Considering the frequency regulation requirements under different scenarios, the proposed parameter setting method can flexibly adjust the integrated virtual inertia control parameters, and maximize the frequency regulation capability of wind turbine on the basis of ensuring operation safety.

Key words： Wind turbine integrated virtual inertia control available frequency regulation energy parameter setting

Received: 14 March 2024

PACS:

TM614

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Li Kexin
	An Jun
	Shi Yan
	Zhou Yibo
	Liu Chuyu

Cite this article:

Li Kexin,An Jun,Shi Yan等. An Integrated Virtual Inertia Control Parameter Setting Method for Wind Turbine Based on Available Frequency Regulation Energy[J]. Transactions of China Electrotechnical Society, 2025, 40(5): 1382-1394.

URL:

https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.240400 OR https://dgjsxb.ces-transaction.com/EN/Y2025/V40/I5/1382

[1] 李军徽, 安晨宇, 李翠萍, 等. 计及调峰市场交易的储能-新能源-火电多目标优化调度[J]. 电工技术学报, 2023, 38(23): 6391-6406.
Li Junhui, An Chenyu, Li Cuiping, et al.Multi-objective optimization scheduling method considering peak regulating market transactions for energy storage-new energy-thermal power[J]. Transactions of China Electrotechnical Society, 2023, 38(23): 6391-6406.
[2] 安军, 周永超, 周毅博, 等. 考虑风荷不确定性的电源无功电压调差系数整定方法研究[J]. 东北电力大学学报, 2023, 43(4): 30-38.
An Jun, Zhou Yongchao, Zhou Yibo, et al.Optimization method for var-voltage adjustment CoefficientConsidering wind power and load uncertainty[J]. Journal of Northeast Electric Power University, 2023, 43(4): 30-38.
[3] Fradley J, Preece R, Barnes M.The influence of network factors on frequency stability[J]. IEEE Transactions on Power Systems, 2020, 35(4): 2826-2834.
[4] 李兆伟, 吴雪莲, 庄侃沁, 等. “9·19” 锦苏直流双极闭锁事故华东电网频率特性分析及思考[J]. 电力系统自动化, 2017, 41(7): 149-155.
Li Zhaowei, Wu Xuelian, Zhuang Kanqin, et al.Analysis and reflection on frequency characteristics of East China grid after bipolar locking of “9·19” Jinping-Sunan DC transmission line[J]. Automation of Electric Power Systems, 2017, 41(7): 149-155.
[5] 方勇杰. 英国“8·9” 停电事故对频率稳定控制技术的启示[J]. 电力系统自动化, 2019, 43(24): 1-5.
Fang Yongjie.Reflections on frequency stability control technology based on the blackout event of 9 August 2019 in UK[J]. Automation of Electric Power Systems, 2019, 43(24): 1-5.
[6] 孙华东, 许涛, 郭强, 等. 英国“8·9” 大停电事故分析及对中国电网的启示[J]. 中国电机工程学报, 2019, 39(21): 6183-6192.
Sun Huadong, Xu Tao, Guo Qiang, et al.Analysis on blackout in great Britain power grid on August 9th, 2019 and its enlightenment to power grid in China[J]. Proceedings of the CSEE, 2019, 39(21): 6183-6192.
[7] 谢震, 杨曙昕, 代鹏程, 等. 构网型全功率风电机组网侧变流器耦合分析及抑制策略[J]. 电工技术学报, 2023, 38(14): 3745-3758, 3768.
Xie Zhen, Yang Shuxin, Dai Pengcheng, et al.Grid-side coupling analysis and suppression strategy of grid-forming full-power wind turbines[J]. Transactions of China Electrotechnical Society, 2023, 38(14): 3745-3758, 3768.
[8] 王勤赫, 边竞, 齐文博, 等. 大规模风电经VSC-HVDC接入的电网频率控制策略[J]. 东北电力大学学报, 2023, 43(4): 74-81.
Wang Qinhe, Bian Jing, Qi Wenbo, et al.The frequency control strategy of the grid connected to large-scale wind power via VSC-HVDC[J]. Journal of Northeast Electric Power University, 2023, 43(4): 74-81.
[9] 张冠锋, 杨俊友, 孙峰, 等. 基于虚拟惯量和频率下垂控制的双馈风电机组一次调频策略[J]. 电工技术学报, 2017, 32(22): 225-232.
Zhang Guanfeng, Yang Junyou, Sun Feng, et al.Primary frequency regulation strategy of DFIG based on virtual inertia and frequency droop control[J]. Transactions of China Electrotechnical Society, 2017, 32(22): 225-232.
[10] Morren J, de Haan S W H, Kling W L, et al. Wind turbines emulating inertia and supporting primary frequency control[J]. IEEE Transactions on Power Systems, 2006, 21(1): 433-434.
[11] 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.
[12] 颜湘武, 崔森, 常文斐. 考虑储能自适应调节的双馈感应发电机一次调频控制策略[J]. 电工技术学报, 2021, 36(5): 1027-1039.
Yan Xiangwu, Cui Sen, Chang Wenfei.Primary frequency regulation control strategy of doubly-fed induction generator considering supercapacitor SOC feedback adaptive adjustment[J]. Transactions of China Electrotechnical Society, 2021, 36(5): 1027-1039.
[13] 王同森, 程雪坤. 计及转速限值的双馈风机变下垂系数控制策略[J]. 电力系统保护与控制, 2021, 49(9): 29-36.
Wang Tongsen, Cheng Xuekun.Variable droop coefficient control strategy of a DFIG considering rotor speed limit[J]. Power System Protection and Control, 2021, 49(9): 29-36.
[14] 王鑫, 杨德健. 基于变系数PI控制的双馈风电机组自适应转速恢复策略[J]. 电工技术学报, 2023, 38(15): 4120-4129.
Wang Xin, Yang Dejian.Adaptive speed recovery strategy of doubly-fed induction generator based on variable PI control coefficient[J]. Transactions of China Electrotechnical Society, 2023, 38(15): 4120-4129.
[15] 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.
[16] Lee J, Muljadi E, Srensen P, et al.Releasable kinetic energy-based inertial control of a DFIG wind power plant[J]. IEEE Transactions on Sustainable Energy, 2016, 7(1): 279-288.
[17] 张峰, 李柏慷, 丁磊. 考虑风电调频能量联动分配的时变调频参数设定方法[J]. 电力系统自动化, 2022, 46(16): 188-197.
Zhang Feng, Li Baikang, Ding Lei.Parameter setting method of time-varing frequency regulation considering linked energy distribution of wind power for frequency regulation[J]. Automation of Electric Power Systems, 2022, 46(16): 188-197.
[18] 彭勃, 张峰, 梁军. 考虑风速分区的风-储系统短期频率响应协同控制策略[J]. 电力系统自动化, 2018, 42(8): 57-65.
Peng Bo, Zhang Feng, Liang Jun.Coordinated control strategy for short-term frequency response of wind-energy storage system considering wind speed partition[J]. Automation of Electric Power Systems, 2018, 42(8): 57-65.
[19] 闵勇, 陈磊, 刘瑞阔, 等. 电力系统频率动态中惯量与惯量响应特性辨析[J]. 中国电机工程学报, 2023, 43(3): 855-868.
Min Yong, Chen Lei, Liu Ruikuo, et al.Analysis on characteristics of inertia and inertial response in power system frequency dynamics[J]. Proceedings of the CSEE, 2023, 43(3): 855-868.
[20] 张祥宇, 胡剑峰, 付媛, 等. 风储联合系统的虚拟惯量需求与协同支撑[J]. 电工技术学报, 2024, 39(3): 672-685.
Zhang Xiangyu, Hu Jianfeng, Fu Yuan, et al.Virtual inertia demand and collaborative support of wind power and energy storage system[J]. Transactions of China Electrotechnical Society, 2024, 39(3): 672-685.
[21] 安军, 盛帅, 周毅博, 等. 基于量测数据的风电场等效虚拟惯量评估方法[J]. 电网技术, 2023, 47(5): 1819-1829.
An Jun, Sheng Shuai, Zhou Yibo, et al.Evaluation of equivalent virtual inertia of wind farm based on measured data[J]. Power System Technology, 2023, 47(5): 1819-1829.
[22] 郭慧, 汪飞, 顾永文, 等. 基于电压分层控制的直流微电网及其储能扩容单元功率协调控制策略[J]. 电工技术学报, 2022, 37(12): 3117-3131.
Guo Hui, Wang Fei, Gu Yongwen, et al.Coordinated power control strategy for DC microgrid and storage expansion unit based on voltage hierarchical control[J]. Transactions of China Electrotechnical Society, 2022, 37(12): 3117-3131.
[23] 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.
[24] 毛志宇, 李培强, 郭思源. 基于自适应时间尺度小波包和模糊控制的复合储能控制策略[J]. 电力系统自动化, 2023, 47(9): 158-165.
Mao Zhiyu, Li Peiqiang, Guo Siyuan.Control strategy of composite energy storage based on wavelet packet with adaptive time scale and fuzzy control[J]. Automation of Electric Power Systems, 2023, 47(9): 158-165.