Optimization of Frequency Control Parameters of Wind Farms Considering Inertia Security Requirement

doi:10.16183/j.cnki.jsjtu.2023.380

Abstract

Abstract:

The inertia and frequency regulation resources in power systems with a high proportion of renewable energy are scarce, resulting in prominent problems of frequency stability. To address these problems, this paper incorporates the potential frequency support capability of wind farms into the frequency control measures of the power grid, and proposes an optimization method for wind farm control parameters that considers the security requirements of system inertia. After a credible disturbance, the system inertia security requirement that meets the frequency stability constraint is calculated based on the transient frequency index limit. Then, the primary frequency regulation capability that wind farms can provide under different wind conditions is modeled with the goal of minimizing the adjustment of wind farm virtual inertia and frequency droop parameters under disturbances, and a dynamic optimization model for wind farm frequency control parameters is established. Finally, the frequency control parameters are calculated and numerical tests are conducted on the modified IEEE RTS-79 system. The results show that the proposed parameter optimization method effectively improves the transient frequency response process of wind farms, which helps enhance the frequency stability margin of the system.

Key words: wind farm, frequency stability, inertia security requirement, virtual inertia, droop parameter

CLC Number:

TM712

LI Hongxin, ZHONG Zuhao, LU Yi, WEN Yunfeng. Optimization of Frequency Control Parameters of Wind Farms Considering Inertia Security Requirement[J]. Journal of Shanghai Jiao Tong University, 2025, 59(3): 323-332.

Figures/Tables 11

Fig.1

Fig.2

Fig.3

Fig.4

Tab.1

Fig.5

Fig.6

Tab.2

Fig.7

Tab.3

Tab.4

References 23

[1]	黄强, 郭怿, 江建华, 等. “双碳”目标下中国清洁电力发展路径[J]. 上海交通大学学报, 2021, 55(12): 1499-1509. doi: 10.16183/j.cnki.jsjtu.2021.272
	HUANG Qiang, GUO Yi, JIANG Jianhua, et al. Development pathway of China’s clean electricity under carbon peaking and carbon neutrality goals[J]. Journal of Shanghai Jiao Tong University, 2021, 55(12): 1499-1509.
[2]	文云峰, 杨伟峰, 林晓煌. 低惯量电力系统频率稳定分析与控制研究综述及展望[J]. 电力自动化设备, 2020, 40(9): 211-222.
	WEN Yunfeng, YANG Weifeng, LIN Xiaohuang. Review and prospect of frequency stability analysis and control of low-inertia power systems[J]. Electric Power Automation Equipment, 2020, 40(9): 211-222.
[3]	汪梦军, 郭剑波, 马士聪, 等. 新能源电力系统暂态频率稳定分析与调频控制方法综述[J]. 中国电机工程学报, 2023, 43(5): 1672-1694.
	WANG Mengjun, GUO Jianbo, MA Shicong, et al. Review of transient frequency stability analysis and frequency regulation control methods for renewable power systems[J]. Proceedings of the CSEE, 2023, 43(5): 1672-1694.
[4]	余威, 杨欢红, 焦伟, 等. 基于优劣解距离算法的光储配电网自适应虚拟惯性控制策略[J]. 上海交通大学学报, 2022, 56(10): 1317-1324. doi: 10.16183/j.cnki.jsjtu.2022.106
	YU Wei, YANG Huanhong, JIAO Wei, et al. Adaptive virtual inertial control strategy of optical storage and distribution network based on TOPSIS algorithm[J]. Journal of Shanghai Jiao Tong University, 2022, 56(10): 1317-1324.
[5]	黄俊凯, 杨知方, 余娟, 等. 面向频率稳定校核的风机快速频率响应低阶建模方法及其误差分析[J]. 中国电机工程学报, 2022, 42(18): 6752-6766.
	HUANG Junkai, YANG Zhifang, YU Juan, et al. Low-order modeling of wind turbine-based fast frequency response and its error analysis for frequency stability assessment[J]. Proceedings of the CSEE, 2022, 42(18): 6752-6766.
[6]	王彤, 邢其鹏, 李鸿恩, 等. 计及虚拟惯量控制的DFIG等效惯量在线评估与响应特性分析[J]. 电力系统保护与控制, 2022, 50(11): 52-60.
	WANG Tong, XING Qipeng, LI Hong’en, et al. Online evaluation and response characteristics analysis of equivalent inertia of a doubly-fed induction generator incorporating virtual inertia control[J]. Power System Protection & Control, 2022, 50(11): 52-60.
[7]	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.
[8]	LI H Y, JU P, GAN C, et al. Analytic analysis for dynamic system frequency in power systems under uncertain variability[J]. IEEE Transactions on Power Systems, 2018, 34(2): 982-993.
[9]	XU G Y, ZHU C, BI T S, et al. Optimal frequency controller parameters of wind turbines participating system frequency control[C]//2018 IEEE Power & Energy Society General Meeting. Portland, USA: IEEE, 2018: 1-5.
[10]	赵冬梅, 许瑞庆, 郑立鑫. 全风况下双馈风机参与调频的协调控制策略研究[J]. 电力系统保护与控制, 2017, 45(12): 53-59.
	ZHAO Dongmei, XU Ruiqing, ZHENG Lixin. Research on coordinated control strategy for DFIGs participating in system frequency regulation with different wind[J]. Power System Protection & Control, 2017, 45(12): 53-59.
[11]	马喜平, 何世恩, 姚寅, 等. 计及风速不确定性及相关性的风电场分区虚拟惯量估计[J]. 电力系统保护与控制, 2022, 50(10): 123-131.
	MA Xiping, HE Shien, YAO Yin, et al. Virtual inertia estimation of wind farm zones with wind speed uncertainty and correlation[J]. Power System Protection & Control, 2022, 50(10): 123-131.
[12]	YOU R, CHAI J Y, SUN X D, et al. Variable speed wind turbine based on electromagnetic coupler and its experimental measurement[C]//2014 IEEE PES General Meeting \| Conference & Exposition. National Harbor, USA: IEEE, 2014: 1-5.
[13]	WANG X, DU W. Virtual inertia control of grid-connected wind farms[C]//International Conference on Renewable Power Generation (RPG 2015). Beijing, China: Institution of Engineering and Technology, 2015.
[14]	张武其, 文云峰, 迟方德, 等. 电力系统惯量评估研究框架与展望[J]. 中国电机工程学报, 2021, 41(20): 6842-6856.
	ZHANG Wuqi, WEN Yunfeng, CHI Fangde, et al. Research framework and prospect on power system inertia estimation[J]. Proceedings of the CSEE, 2021, 41(20): 6842-6856.
[15]	王宝财, 孙华东, 李文锋, 等. 考虑动态频率约束的电力系统最小惯量评估[J]. 中国电机工程学报, 2022, 42(1): 114-127.
	WANG Baocai, SUN Huadong, LI Wenfeng, et al. Minimum inertia estimation of power system considering dynamic frequency constraints[J]. Proceedings of the CSEE, 2022, 42(1): 114-127.
[16]	刘中建, 周明, 李昭辉, 等. 高比例新能源电力系统的惯量控制技术与惯量需求评估综述[J]. 电力自动化设备, 2021, 41(12): 1-11.
	LIU Zhongjian, ZHOU Ming, LI Zhaohui, et al. Review of inertia control technology and requirement evaluation in renewable-dominant power system[J]. Electric Power Automation Equipment, 2021, 41(12): 1-11.
[17]	国家市场监督管理总局, 国家标准化管理委员会. 电力系统安全稳定计算规范: GB/T 40581—2021[S]. 北京: 中国标准出版社, 2021.
	State Administration for Market Regulation, National Standardization Administration of the People’s Republic of China. Calculation specification for power system security and stability: GB/T 40581—2021[S]. Beijing: Standards Press of China, 2021.
[18]	林晓煌, 文云峰, 杨伟峰. 惯量安全域: 概念、特点及评估方法[J]. 中国电机工程学报, 2021, 41(9): 3065-3079.
	LIN Xiaohuang, WEN Yunfeng, YANG Weifeng. Inertia security region: Concept, characteristics, and assessment method[J]. Proceedings of the CSEE, 2021, 41(9): 3065-3079.
[19]	张英敏, 彭泽峰, 彭乔, 等. 预测新能源接入电网受扰后频率最低点的通用ASF模型[J]. 电网技术, 2023, 47(5): 1788-1799.
	ZHANG Yingmin, PENG Zefeng, PENG Qiao, et al. Generic ASF model of new-energy-integrated power grid for frequency nadir estimation under disturbance[J]. Power System Technology, 2023, 47(5): 1788-1799.
[20]	罗魁, 郭剑波, 王伟胜, 等. 跟网型新能源附加频率控制对频率稳定及小扰动同步稳定影响分析综述[J]. 中国电机工程学报, 2023, 43(4): 1262-1281.
	LUO Kui, GUO Jianbo, WANG Weisheng, et al. Review of impact of grid following variable renewable energy supplementary frequency control on frequency stability and small-disturbance synchronization stability[J]. Proceedings of the CSEE, 2023, 43(4): 1262-1281.
[21]	SHI Q M, WANG G, MA W M, et al. Coordinated virtual inertia control strategy for D-PMSG considering frequency regulation ability[J]. Journal of Electrical Engineering & Technology, 2016, 11(6): 1556-1570.
[22]	韩帅, 张峰, 丁磊, 等. 基于混合Copula函数的风电场可用惯量评估方法[J]. 电力自动化设备, 2021, 41(3): 189-195.
	HAN Shuai, ZHANG Feng, DING Lei, et al. Available inertia evaluation method of wind farm based on mixed Copula function[J]. Electric Power Automation Equipment, 2021, 41(3): 189-195.
[23]	SHI Z, XU Y, WANG Y, et al. Coordinating multiple resources for emergency frequency control in the energy receiving-end power system with HVDCs[J]. IEEE Transactions on Power Systems, 2023, 38(5): 4708-4723.

风电场	中低风况		高风况		风电场	中低风况		高风况
风电场	H_vir	k_w	H_vir	k_w	风电场	H_vir	k_w	H_vir	k_w
W2	[1, 3.5]	[10, 40]	[2.5, 6]	[20, 70]	W15	[1, 3]	[10, 40]	[2, 4.5]	[25, 75]
W4	[1, 5]	[20, 50]	[3, 8.5]	[30, 80]	W19	[1, 3]	[10, 40]	[2, 4.5]	[25, 75]
W7	[1, 5]	[20, 50]	[3, 8.5]	[30, 80]	W24	[1, 5]	[20, 50]	[3, 8.5]	[35, 85]
W9	[1, 5]	[25, 55]	[3.5, 8]	[35, 85]	W27	[1, 5]	[20, 50]	[3, 8.5]	[30, 80]
W12	[1, 6]	[30, 60]	[5, 9]	[40, 90]	W29	[1, 5]	[20, 50]	[4, 7.5]	[35, 85]

参数	W2	W4	W7	W9	W12
H_vir	2.871	4.592	4.492	4.615	5.934
k_w	38.153	43.709	43.709	43.709	46.487
参数	W15	W19	W24	W27	W29
H_vir	2.323	2.323	4.592	4.592	4.592
k_w	38.153	38.153	43.709	43.709	43.709

场景	R_{oCoF_max}/ (Hz·s^-1)	f_m/ Hz	f_ss/Hz
风电不参与调频	0.65	49.19	49.65
风电参数优化前指标	0.56	49.56	49.74
风电参数优化后指标	0.43	49.72	49.81
安全限值	0.50	49.60	49.80

运行状态	极限扰动量/%	系统惯量安全需求/(MW·s)
原始系统	-5.7	14623.62
中低风况	-8.1	23265.20
高风况	-9.2	29412.97