Abstract After large-scale wind turbines and energy storage are connected to the grid, the inertia of the system will be seriously weakened, affecting the stable and safe operation of the frequency. The decoupling characteristics of rotational speed and frequency of DFIG make it unable to respond to the frequency changes of the grid. As a stationary non-rotating component, the energy storage does not have the inertia response capability of the synchronous generator. To improve the virtual inertia support function of new energy high penetration regional grid, this paper uses the energy of wind turbine and energy storage to broaden the inertia source for the system, reasonably allocates the frequency regulation tasks of wind turbine and energy storage in the inertia response period, and proposes a wind turbine-storage virtual inertia cooperative support control method based on the frequency safety demand. Firstly, the frequency response of DFIG and battery is analyzed, the virtual inertia of DFIG and battery is defined, and the frequency response model of the system with virtual inertia is established. Then, the effect of virtual inertia control on the frequency characteristics of the system is analyzed, a method for calculating the inertia response time of the system is proposed,which is used as a start-stop condition for virtual inertial control, and the inertia requirement of the system is evaluated , which is based on the safety constraint of rate of change of frequency. Finally, a collaborative wind-storage virtual inertia control strategy based on the inertia demand of system is proposed, the frequency modulation tasks of the wind and storage energy are reasonably allocated, the controller parameters are completed, and the inertia response time is used to block the controller in time, effectively avoiding the frequency overshoot problem. Simulation analysis of the proposed virtual inertia cooperative support control strategy shows that, under the proposed control strategy, when the disturbance power is small, the inertia response capability of the wind turbine is given full play, without the need for additional energy storage to respond to frequency changes, reducing the number of energy storage charges and discharges,which is conducive to extending the service life of the energy storage; When the disturbance power is large, the wind turbine and energy storage jointly participate in frequency regulation, and the energy storage starts the virtual inertia control to make up for the power shortage, which meets the frequency support demand by reasonably calling the inertia reserve of the wind turbine and energy storage, and the wind storage virtual inertia additional controller can be withdrawn in time within the specified time, which reduces the overshoot in the frequency recovery process and effectively improves the frequency stability and safety. The following conclusions can be drawn from the simulation analysis: (1) Wind power and energy storage using virtual inertia controller can simulate the inertia response of synchronous generator units, but virtual inertia control has a negative impact on the frequency response characteristics during the frequency recovery period, and there is a frequency overshoot problem, which is not conducive to frequency recovery. (2) The inertia response time can be used as a blocking condition for the wind storage virtual inertia controller, and the virtual inertia control of both wind turbine and energy storage can be withdrawn in time under the proposed time, which effectively avoids the frequency fluctuation problem caused by inertia overshoot during the frequency recovery period.(3) Under the proposed virtual inertia cooperative control strategy, the frequency modulation tasks of the wind and storage energy are reasonably allocated to meet the minimum inertia demand of the system, which fully releases the potential of wind power and energy storage to support the frequency. By simulating and comparing the frequency regulation effect when no additional control, conventional differential control and wind-storage virtual inertia cooperative control, it is verified that the proposed control can meet the frequency support requirement more reliably under the premise of reasonable invocation of wind-storage inertia reserve.
Zhang Xiangyu,Hu Jianfeng,Fu Yuan等. Virtual Inertia Demand and Collaborative Support of Wind Power and Energy Storage System[J]. Transactions of China Electrotechnical Society, 2024, 39(3): 672-685.
[1] 李军徽, 冯喜超, 严干贵, 等. 高风电渗透率下的电力系统调频研究综述[J]. 电力系统保护与控制, 2018, 46(2): 163-170. Li Junhui, Feng Xichao, Yan Gangui, et al.Survey on frequency regulation technology in high wind penetration power system[J]. Power System Protection and Control, 2018, 46(2): 163-170. [2] 付媛, 王毅, 张祥宇, 等. 变速风电机组的惯性与一次调频特性分析及综合控制[J]. 中国电机工程学报, 2014, 34(27): 4706-4716. Fu Yuan, Wang Yi, Zhang Xiangyu, et al.Analysis and integrated control of inertia and primary frequency regulation for variable speed wind turbines[J]. Proceedings of the CSEE, 2014, 34(27): 4706-4716. [3] 龚浩岳, 周勤勇, 郭强, 等. 高比例新能源接入场景电力系统频率分析模型改进与应用[J]. 电网技术, 2021, 45(12): 4603-4612. Gong Haoyue, Zhou Qinyong, Guo Qiang, et al.Improvement and application of frequency analysis modules for power system in high proportion of renewable energy situation[J]. Power System Technology, 2021, 45(12): 4603-4612. [4] 曾辉, 孙峰, 李铁, 等. 澳大利亚“9·28” 大停电事故分析及对中国启示[J]. 电力系统自动化, 2017, 41(13): 1-6. Zeng Hui, Sun Feng, Li Tie, et al.Analysis of “9·28” blackout in South Australia and its enlightenment to China[J]. Automation of Electric Power Systems, 2017, 41(13): 1-6. [5] 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. [6] 张靖, 张志文, 胡斯佳, 等. 独立微电网风储协同调频的功率柔性分配策略[J]. 电工技术学报, 2022, 37(15): 3767-3780. Zhang Jing, Zhang Zhiwen, Hu Sijia, et al.A flexible power distribution strategy with wind turbine generator and energy storage for frequency regulation in isolated microgrid[J]. Transactions of China Electrotechnical Society, 2022, 37(15): 3767-3780. [7] 李军徽, 侯涛, 穆钢, 等. 电力市场环境下考虑风电调度和调频极限的储能优化控制[J]. 电工技术学报, 2021, 36(9): 1791-1804. Li Junhui, Hou Tao, Mu Gang, et al.Optimal control strategy for energy storage considering wind farm scheduling plan and modulation frequency limitation under electricity market environment[J]. Transactions of China Electrotechnical Society, 2021, 36(9): 1791-1804. [8] 张祥宇, 付媛, 王毅, 等. 含虚拟惯性与阻尼控制的变速风电机组综合PSS控制器[J]. 电工技术学报, 2015, 30(1): 159-169. Zhang Xiangyu, Fu Yuan, Wang Yi, et al.Integrated PSS controller of variable speed wind turbines with virtual inertia and damping control[J]. Transactions of China Electrotechnical Society, 2015, 30(1): 159-169. [9] 王科, 秦文萍, 张宇, 等. 双馈风机等效惯量控制比例系数对系统功角首摆稳定的影响机理分析[J]. 电工技术学报, 2023, 38(3): 741-753. Wang Ke, Qin Wenping, Zhang Yu, et al.Mechanism analysis of the influence of proportional coefficient of equivalent inertia control of doubly-fed fan on the stability of power angle first swing of the system[J]. Transactions of China Electrotechnical Society, 2023, 38(3): 741-753. [10] 张祥宇, 李凌斐, 边子轩. 基于混合静止能量的虚拟转动惯量控制技术[J]. 电力自动化设备, 2019, 39(11): 50-56. Zhang Xiangyu, Li Lingfei, Bian Zixuan.Virtual moment inertia control based on hybrid static energy storage[J]. Electric Power Automation Equipment, 2019, 39(11): 50-56. [11] Tian Xinshou, Wang Weisheng, Chi Yongning, et al.Virtual inertia optimisation control of DFIG and assessment of equivalent inertia time constant of power grid[J]. IET Renewable Power Generation, 2018, 12(15): 1733-1740. [12] 李和明, 张祥宇, 王毅, 等. 基于功率跟踪优化的双馈风力发电机组虚拟惯性控制技术[J]. 中国电机工程学报, 2012, 32(7): 32-39, 188. Li Heming, Zhang Xiangyu, Wang Yi, et al.Virtual inertia control of DFIG-based wind turbines based on the optimal power tracking[J]. Proceedings of the CSEE, 2012, 32(7): 32-39, 188. [13] Miao Zhixin, Fan Lingling, Osborn D, et al.Wind farms with HVDC delivery in inertial response and primary frequency control[J]. IEEE Transactions on Energy Conversion, 2010, 25(4): 1171-1178. [14] 林俐, 李晓钰, 王世谦, 等. 基于分段控制的双馈风电机组有功-频率控制[J]. 中国电力, 2012, 45(2): 49-53. Lin Li, Li Xiaoyu, Wang Shiqian, et al.An active power-frequency control strategy of a DFIG based on subsection control[J]. Electric Power, 2012, 45(2): 49-53. [15] 潘文霞, 全锐, 王飞. 基于双馈风电机组的变下垂系数控制策略[J]. 电力系统自动化, 2015, 39(11): 126-131, 186. Pan Wenxia, Quan Rui, Wang Fei.A variable droop control strategy for doubly-fed induction generators[J]. Automation of Electric Power Systems, 2015, 39(11): 126-131, 186. [16] Liu Jia, Miura Y, Ise T.Comparison of dynamic characteristics between virtual synchronous generator and droop control in inverter-based distributed generators[J]. IEEE Transactions on Power Electronics, 2016, 31(5): 3600-3611. [17] 邢鹏翔, 付立军, 王刚, 等. 改善微电网频率动态响应的虚拟同步发电机强化惯量控制方法[J]. 高电压技术, 2018, 44(7): 2346-2353. Xing Pengxiang, Fu Lijun, Wang Gang, et al.Control strategy of virtual synchronous generator with enhanced inertia for improving dynamic frequency response of microgrid[J]. High Voltage Engineering, 2018, 44(7): 2346-2353. [18] 陈萌, 肖湘宁, 赖柏竹. 基于虚拟同步发电机控制的微电网分层频率控制[J]. 高电压技术, 2018, 44(4): 1278-1284. Chen Meng, Xiao Xiangning, Lai Baizhu.Hierarchical frequency control strategy of microgrids with virtual synchronous generators[J]. High Voltage Engineering, 2018, 44(4): 1278-1284. [19] Wong W C, Chung C Y.Coordinated damping control design for DFIG-based wind generation considering power output variation[J]. IEEE Transactions on Power Systems, 2012, 27(4): 1916-1925. [20] 杨丘帆, 王琛淇, 魏俊红, 等. 提升电网惯性与一次调频性能的储能容量配置方法[J]. 电力建设, 2020, 41(10): 116-124. Yang Qiufan, Wang Chenqi, Wei Junhong, et al.Configuration method of energy storage capacity for improving grid inertia and primary frequency modulation performance[J]. Electric Power Construction, 2020, 41(10): 116-124. [21] 刘巨, 姚伟, 文劲宇, 等. 一种基于储能技术的风电场虚拟惯量补偿策略[J]. 中国电机工程学报, 2015, 35(7): 1596-1605. Liu Ju, Yao Wei, Wen Jinyu, et al.A virtual inertia compensation strategy for wind farm based on energy storage technology[J]. Proceedings of the CSEE, 2015, 35(7): 1596-1605. [22] 吴启帆, 宋新立, 张静冉, 等. 电池储能参与电网一次调频的自适应综合控制策略研究[J]. 电网技术, 2020, 44(10): 3829-3836. Wu Qifan, Song Xinli, Zhang Jingran, et al.Research on adaptive comprehensive control strategy of battery energy storage participating in primary frequency regulation of power grid[J]. Power System Technology, 2020, 44(10): 3829-3836. [23] 姜惠兰, 蔡继朝, 肖瑞, 等. 一种提高系统频率响应特性的风储协调控制策略[J]. 电力自动化设备, 2021, 41(7): 44-51. Jiang Huilan, Cai Jizhao, Xiao Rui, et al.A wind-storage coordinated control strategy for improving system frequency response characteristics[J]. Electric Power Automation Equipment, 2021, 41(7): 44-51. [24] 颜湘武, 孙雪薇, 崔森, 等. 考虑系统频率连续波动与二次跌落的双馈风力发电机组虚拟惯量通用控制策略[J]. 太阳能学报, 2021, 42(11): 247-254. Yan Xiangwu, Sun Xuewei, Cui Sen, et al.Virtual inertia general control strategy of dfig-based wind turbine considering continuous fluctuation of system frequency and second frequency drop[J]. Acta Energiae Solaris Sinica, 2021, 42(11): 247-254. [25] Sun Ming, Min Yong, Chen Lei, et al.Optimal auxiliary frequency control of wind turbine generators and coordination with synchronous generators[J]. CSEE Journal of Power and Energy Systems, 2020, 7(1): 78-85. [26] 赵晶晶, 李敏, 何欣芹, 等. 基于限转矩控制的风储联合调频控制策略[J]. 电工技术学报, 2019, 34(23): 4982-4990. Zhao Jingjing, Li Min, He Xinqin, et al.Coordinated control strategy of wind power and energy storage in frequency regulation based on torque limit control[J]. Transactions of China Electrotechnical Society, 2019, 34(23): 4982-4990. [27] 刘彬彬, 杨健维, 廖凯, 等. 基于转子动能控制的双馈风电机组频率控制改进方案[J]. 电力系统自动化, 2016, 40(16): 17-22. Liu Binbin, Yang Jianwei, Liao Kai, et al.Improved frequency control strategy for DFIG-based wind turbines based on rotor kinetic energy control[J]. Automation of Electric Power Systems, 2016, 40(16): 17-22. [28] 唐西胜, 苗福丰, 齐智平, 等. 风力发电的调频技术研究综述[J]. 中国电机工程学报, 2014, 34(25): 4304-4314. Tang Xisheng, Miao Fufeng, Qi Zhiping, et al.Survey on frequency control of wind power[J]. Proceedings of the CSEE, 2014, 34(25): 4304-4314. [29] 兰飞, 潘益丰, 时萌, 等. 双馈风电机组变系数虚拟惯量优化控制[J]. 电力系统自动化, 2019, 43(12): 51-59. Lan Fei, Pan Yifeng, Shi Meng, et al.Optimal variable-coefficient virtual inertia control for DFIG-based wind turbines[J]. Automation of Electric Power Systems, 2019, 43(12): 51-59. [30] 张祥宇, 杨黎, 朱晓荣, 等. 光储发电系统的虚拟转动惯量控制[J]. 电力自动化设备, 2017, 37(9): 109-115. Zhang Xiangyu, Yang Li, Zhu Xiaorong, et al.Virtual rotational inertia control of PV generation system with energy storage devices[J]. Electric Power Automation Equipment, 2017, 37(9): 109-115. [31] 武龙星, 庞辉, 晋佳敏, 等. 基于电化学模型的锂离子电池荷电状态估计方法综述[J]. 电工技术学报, 2022, 37(7): 1703-1725. Wu Longxing, Pang Hui, Jin Jiamin, et al.A review of SOC estimation methods for lithium-ion batteries based on electrochemical model[J]. Transactions of China Electrotechnical Society, 2022, 37(7): 1703-1725. [32] Polajžer B, Dolinar D, Ritonja J.Estimation of area’s frequency response characteristic during large frequency changes using local correlation[J]. IEEE Transactions on Power Systems, 2016, 31(4): 3160-3168. [33] 郭小龙, 毕天姝, 刘方蕾, 等. 风、光高渗透率电网中考虑频率稳定的可再生能源承载力研究[J]. 可再生能源, 2020, 38(1): 84-90. Guo Xiaolong, Bi Tianshu, Liu Fanglei, et al.Estimating maximum penetration level of renewable energy based on frequency stability constrains in networks with high-penetration wind and photovoltaic energy[J]. Renewable Energy Resources, 2020, 38(1): 84-90. [34] 杨森, 杜文娟, 王旭斌, 等. 风火-需求侧响应协调频率控制方法[J]. 电网技术, 2017, 41(3): 845-853. Yang Sen, Du Wenjuan, Wang Xubin, et al.Coordinated frequency control method of wind/ thermal/demand response[J]. Power System Technology, 2017, 41(3): 845-853.
2024, Vol. 39 
