Research on wind-storage self-synchronizing frequency regulation strategy based on intermediate layer control

doi:10.3969/j.issn.2097-0706.2025.08.003

Abstract

Abstract:

With the continuous expansion of power grids and increasing penetration of renewable energy， wind power， as a key component of clean energy， plays an increasingly important role in power grid frequency regulation. However， the volatility and intermittency of wind power pose new challenges to traditional grid frequency regulation strategies. To address this issue， the strategy of energy storage-based virtual synchronous frequency regulation was analyzed， with an in-depth investigation of wind-storage integrated primary frequency regulation control technology. An adaptive inertia response control method， based on variable coefficient bang-bang control， was employed to optimize the allocation of frequency regulation power. A wind-storage integrated frequency regulation control strategy based on intermediate layer was proposed to achieve more efficient control through hierarchical management. The simulation results showed that the proposed strategy effectively regulated grid frequency during fluctuations and reduced frequency deviations. It optimized the allocation of frequency regulation power between wind farm and energy storage system during changes in grid frequency， significantly enhancing the stability and reliability of the power system.

Key words: wind farm, energy storage system, wind-storage integration, primary frequency regulation, virtual synchronous frequency regulation control, variable coefficient bang-bang control, adaptive inertia response control, frequency regulation power allocation

CLC Number:

TK01：TM614

ZHEN Wenxi, MA Xiping, DAI Yuehong, NIU Wei, CHEN Baixu, ZENG Gui. Research on wind-storage self-synchronizing frequency regulation strategy based on intermediate layer control[J]. Integrated Intelligent Energy, 2025, 47(8): 21-29.

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References 27

[1]	王少波. 风储联合一次调频控制策略研究[D]. 呼和浩特: 内蒙古工业大学, 2023.
	WANG Shaobo. Research on primary frequency modulation control strategy of wind storage combined with wind storage[D]. Hohhot: Inner Mongolia University of Technology, 2023.
[2]	商侨晏, 李凤婷, 王森, 等. 基于多变量模糊逻辑控制的风储联合系统一次调频策略[J]. 电网技术, 2023, 47(6): 2344-2360.
	SHANG Qiaoyan, LI Fengting, WANG Sen, et al. Primary frequency modulation strategy for wind-storage combined system based on multivariable fuzzy logic control[J]. Power System Technology, 2023, 47(6): 2344-2360.
[3]	李忠文, 吴龙, 程志平, 等. 光储系统参与微电网频率调节的模糊自适应滑模控制[J]. 高电压技术, 2022, 48(6): 2065-2076.
	LI Zhongwen, WU Long, CHENG Zhiping, et al. Fuzzy adaptive sliding mode control of photovoltaic and storage systems for providing frequency regulation of microgrid[J]. High Voltage Engineering, 2022, 48(6): 2065-2076.
[4]	娄为, 翟海保, 许凌, 等. 风电-储能-电动汽车联合调频控制策略研究[J]. 可再生能源, 2021, 39(12): 1648-1654.
	LOU Wei, ZHAI Haibao, XU Ling, et al. Research on control strategy of WG-ESS-PEV joint frequency modulation[J]. Renewable Energy Resources, 2021, 39(12): 1648-1654.
[5]	朱瑛, 秦立宽, 颜全椿, 等. 考虑频率响应过程的风储联合调频策略及储能系统优化配置方法[J]. 电力自动化设备, 2021, 41(10): 28-35.
	ZHU Ying, QIN Likuan, YAN Quanchun, et al. Wind-storage combined frequency regulation strategy and optimal configuration method of energy storage system considering process of frequency response[J]. Electric Power Automation Equipment, 2021, 41(10): 28-35.
[6]	赵长伟, 王慧, 顾志成, 等. 分散式风储系统频率和电压调节能力评估关键技术[J]. 综合智慧能源, 2024, 46(6): 78-87. doi: 10.3969/j.issn.2097-0706.2024.06.009
	ZHAO Changwei, WANG Hui, GU Zhicheng, et al. Key technologies of the evaluation on distributed wind-storage systems' frequency and voltage regulation capacities[J]. Integrated Intelligent Energy, 2024, 46(6): 78-87. doi: 10.3969/j.issn.2097-0706.2024.06.009
[7]	苗福丰, 唐西胜, 齐智平. 储能参与风电一次调频的容量优化[J]. 电工电能新技术, 2016, 35(4): 23-29.
	MIAO Fufeng, TANG Xisheng, QI Zhiping. Capacity optimization of energy storage participating to wind plant primary frequency regulation[J]. Advanced Technology of Electrical Engineering and Energy, 2016, 35(4): 23-29.
[8]	严干贵, 王昱博, 钟诚, 等. 风储联合系统调频控制策略研究[J]. 电力建设, 2016, 37(12): 55-60. doi: 10.3969/j.issn.1000－7229.2016.12.007
	YAN Gangui, WANG Yubo, ZHONG Cheng, et al. Frequency control strategy for wind storage combined system[J]. Electric Power Construction, 2016, 37(12): 55-60. doi: 10.3969/j.issn.1000－7229.2016.12.007
[9]	刘辉, 葛俊, 巩宇, 等. 风电场参与电网一次调频最优方案选择与风储协调控制策略研究[J]. 全球能源互联网, 2019, 2(1): 44-52.
	LIU Hui, GE Jun, GONG Yu, et al. Optimization scheme selection of wind farm participation in grid primary frequency modulation and study of wind-storage coordination control strategy[J]. Journal of Global Energy Interconnection, 2019, 2(1): 44-52.
[10]	胡泽春, 夏睿, 吴林林, 等. 考虑储能参与调频的风储联合运行优化策略[J]. 电网技术, 2016, 40(8): 2251-2257.
	HU Zechun, XIA Rui, WU Linlin, et al. Joint operation optimization of wind-storage union with energy storage participating frequency regulation[J]. Power System Technology, 2016, 40(8): 2251-2257.
[11]	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.
[12]	匡生, 王蓓蓓. 考虑储能寿命和参与调频服务的风储联合运行优化策略[J]. 发电技术, 2020, 41(1): 73-78. doi: 10.12096/j.2096-4528.pgt.19161
	KUANG Sheng, WANG Beibei. Optimization strategy of wind storage joint operation considering energy storage life and participating in frequency modulation service[J]. Power Generation Technology, 2020, 41(1): 73-78. doi: 10.12096/j.2096-4528.pgt.19161
[13]	屈涛涛, 綦晓, 蒋文珂, 等. 考虑风电机组虚拟惯量的新型电力系统频率分布式模型预测控制策略[J]. 综合智慧能源, 2022, 44(10): 25-32. doi: 10.3969/j.issn.2097-0706.2022.10.004
	QU Taotao, QI Xiao, JIANG Wenke, et al. Frequency distributed model predictive control strategy for the new power system considering virtual inertia of wind turbines[J]. Integrated Intelligent Energy, 2022, 44(10): 25-32. doi: 10.3969/j.issn.2097-0706.2022.10.004
[14]	何光层, 张栋梁, 朱红杰, 等. 考虑风储协调运行的频率控制策略研究[J]. 电工技术, 2020(11): 9-13, 147.
	HE Guangceng, ZHANG Dongliang, ZHU Hongjie, et al. Research on frequency control strategy considering coordinated operation of wind power storage[J]. Electric Engineering, 2020(11): 9-13, 147.
[15]	彭勃. 提升风电主动调频能力的风-储协同运行策略研究[D]. 济南: 山东大学, 2020.
	PENG Bo. Study on wind-storage cooperative operation strategy for improving active frequency modulation capability of wind power[D]. Jinan: Shandong University, 2020.
[16]	解妍. 基于模型预测的风力发电系统控制策略研究[D]. 合肥: 合肥工业大学, 2021.
	XIE Yan. Research on control strategy of wind power generation system based on model prediction[D]. Hefei: Hefei University of Technology, 2021.
[17]	杨伟峰, 文云峰, 张武其, 等. 基于风-储联合的双层频率响应控制策略[J]. 电力系统自动化, 2022, 46(12): 184-193.
	YANG Weifeng, WEN Yunfeng, ZHANG Wuqi, et al. Bi-level frequency response control strategy based on wind power and energy storage[J]. Automation of Electric Power Systems, 2022, 46(12): 184-193.
[18]	马玉路. 风储联合运行参与电网一次调频优化控制技术[D]. 淄博: 山东理工大学, 2022.
	MA Yulu. Optimal control technology of wind and storage combined operation participating in primary frequency regulation of power grid[D]. Zibo: Shandong University of Technology, 2022.
[19]	杨易茗. 基于自适应系数的双馈风电机组调频控制策略及参数优化[J]. 电气应用, 2024, 43(5): 40-49.
	YANG Yiming. Parameter economic optimization based on variable coefficient frequency modulation control strategy of double-fed wind turbine[J]. Electrotechnical Application, 2024, 43(5): 40-49.
[20]	孙娜, 董海鹰, 陈薇, 等. 新型电力系统场景下网侧规模化储能二次调频控制策略[J]. 综合智慧能源, 2024, 46(2): 59-67. doi: 10.3969/j.issn.2097-0706.2024.02.008
	SUN Na, DONG Haiying, CHEN Wei, et al. Secondary frequency modulation control strategy for large-scale grid-side energy storage devices in new power systems[J]. Integrated Intelligent Energy, 2024, 46(2): 59-67. doi: 10.3969/j.issn.2097-0706.2024.02.008
[21]	蔡继朝. 风电并网对电力系统频率特性影响及控制策略研究[D]. 天津: 天津大学, 2020.
	CAI Jizhao. Influence of wind power grid connection on frequency characteristics of power system and its control strategy[D]. Tianjin: Tianjin University, 2020.
[22]	王晓东, 李凯凯, 刘颖明, 等. 基于状态观测器的风电机组单机储能系统虚拟惯量控制[J]. 电工技术学报, 2018, 33(6): 1257-1264.
	WANG Xiaodong, LI Kaikai, LIU Yingming, et al. Virtual inertia control of energy storage system in wind turbine based on extended state observer[J]. Transactions of China Electrotechnical Society, 2018, 33(6): 1257-1264.
[23]	左芸裴, 王德林, 周鑫, 等. 基于虚拟惯量和阻尼参数自适应策略的直流微网电压控制研究[J]. 太阳能学报, 2023, 44(11): 485-494. doi: 10.19912/j.0254-0096.tynxb.2022-1040
	ZUO Yunpei, WANG Delin, ZHOU Xin, et al. Research on voltage regulation control of DC microgrid based on virtual inertia and damping parameters' adaptive strategy[J]. Acta Energiae Solaris Sinica, 2023, 44(11): 485-494. doi: 10.19912/j.0254-0096.tynxb.2022-1040
[24]	李雪萍, 王自力, 陈燕东, 等. 基于虚拟惯量模糊自适应的新能源逆变器频率主动支撑策略[J]. 电力系统保护与控制, 2024, 52(20): 25-37.
	LI Xueping, WANG Zili, CHEN Yandong, et al. Active frequency support strategy for new energy inverters based on virtual inertia fuzzy adaptive control[J]. Power System Protection and Control, 2024, 52(20): 25-37.
[25]	张宝锋, 宋子琛, 王剑彬, 等. 风储一体化系统无功响应技术研究[J]. 热力发电, 2024, 53(8): 135-142.
	ZHANG Baofeng, SONG Zichen, WANG Jianbin, et al. Reactive power response technology of wind-storage integrated system[J]. Thermal Power Generation, 2024, 53(8): 135-142.
[26]	王晓东, 郑帅, 刘颖明, 等. 基于储能系统SOC反馈调节的变参数风电场虚拟惯量补偿控制[J]. 电器与能效管理技术, 2017(13): 8-15.
	WANG Xiaodong, ZHENG Shuai, LIU Yingming, et al. Virtual inertia compensation control of wind farm based on SOC feedback regulation of energy storage system[J]. Electrical & Energy Management Technology, 2017(13): 8-15.
[27]	TU S Z, YANG J, ZHAO L, et al. Filtering Chinese microblog topics noise algorithm based on a semi-supervised model[J]. Journal of Tsinghua University (Science and Technology Edition), 2019, 59(3): 178-185.