Estimation of Wind Farm Available Inertia Considering Uncertainty of Wind Speed Distribution and Unit Inertia Transformation

doi:10.16183/j.cnki.jsjtu.2021.S2.008

Abstract

Abstract:

Taking into account the wind speed distribution and correlation, the units in the field are first clustered according to the wind speed distribution, and the wind speed distribution modeling scheme is proposed for practical applications. Then, each area is selected according to the European distance. Finally, considering the uncertainty between wind speed and available inertia, neural network is used to predict the available inertia distribution of each cluster. A wind farm in China is selected as the simulation example. The simulation results show that compared with the equivalent machine method based on average wind speed, the prediction accuracy of the proposed method in the low wind speed range is significantly improved, and the calculation efficiency of the proposed algorithm based on the clustered central unit is higher.

Key words: wind speed forecast, Copula function, virtual inertia, data driven

CLC Number:

TM76

GONG Weizheng, XU Ling, YAO Yin. Estimation of Wind Farm Available Inertia Considering Uncertainty of Wind Speed Distribution and Unit Inertia Transformation[J]. Journal of Shanghai Jiao Tong University, 2021, 55(S2): 51-59.

Figures/Tables 12

Fig.1

Fig.2

Tab.1

Tab.2

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

Tab.3

Fig.8

Fig.9

References 13

[1]	徐贤, 陆晓, 周挺, 等. 华东电网一次调频能力量化评估及运行控制策略[J]. 电力工程技术, 2021, 40(2): 205-211.
	XU Xian, LU Xiao, ZHOU Ting, et al. Evaluation method and operation control strategy of primary frequency response for East China Grid[J]. Electric Power Engineering Technology, 2021, 40(2): 205-211.
[2]	王天翔, 程雪坤, 李伟超, 等. 基于变参数减载控制的风电场一次调频策略[EB/OL]. (2021-06-21) [2021-09-06].https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CAPJ&dbname=CAPJLAST&filename=ZGDL20210621001&uniplatform=NZKPT&v=XIVIlXlPfckgEC-hIP4f10mutzDXohPoxwcdomFWgdKkKpLfSXIc5BdNEaZF2kW_.
	WANG Tianxiang, CHENG Xuekun, LI Weichao, et al. Primary frequency control strategy of wind farm based on variable parameter control[EB/OL]. (2021-06-21) [2021-09-06].https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CAPJ&dbname=CAPJLAST&filename=ZGDL20210621001&uniplatform=NZKPT&v=XIVIlXlPfckgEC-hIP4f10mutzDXohPoxwcdomFWgdKkKpLfSXIc5BdNEaZF2kW_.
[3]	兰飞, 周立. 基于减载功率跟踪曲线切换的风电机组调频策略[J]. 电网与清洁能源, 2020, 36(11): 118-126.
	LAN Fei, ZHOU Li. Frequency regulation strategy of wind turbines based on deloading power tracking curve switching[J]. Power System and Clean Energy, 2020, 36(11): 118-126.
[4]	欧阳金鑫, 袁毅峰, 李梦阳, 等. 考虑风电减载调频的高比例风电电力系统优化调度方法[J]. 电网技术, 2021, 45(6): 2192-2201.
	OUYANG Jinxin, YUAN Yifeng, LI Mengyang, et al. Optimal dispatching method of high-proportion wind power systems considering wind power reserve for frequency adjustment[J]. Power System Technology, 2021, 45(6): 2192-2201.
[5]	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. doi: 10.1109/TSTE.2015.2493165 URL
[6]	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(Sup.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(Sup.1): 179-190.
[7]	DAVID N, WANG Z Y. Physical rotor inertia of DFIG wind turbines for short-term frequency regulation in low-inertia grids[C]// 2017 IEEE Power & Energy Society General Meeting. Chicago, USA: IEEE, 2017: 1-5.
[8]	李世春, 徐松林, 李惠子, 等. 风电场等效虚拟惯量快速估计方法[EB/OL]. (2021-08-02) [2021-09-06]. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CAPJ&dbname=CAPJLAST&filename=DWJS20210730001&uniplatform=NZKPT&v=chvihHo5Q36siJ-kcOd_j_pYaRhDbSsDn_NzbrGevSGPoGwuXQtXkrkgD6t_eH12.
	LI Shichun, XU Songlin, LI Huizi, et al. 风电场等效虚拟惯量快速估计方法[EB/OL]. (2021-08-02) [2021-09-06]. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CAPJ&dbname=CAPJLAST&filename=DWJS20210730001&uniplatform=NZKPT&v=chvihHo5Q36siJ-kcOd_j_pYaRhDbSsDn_NzbrGevSGPoGwuXQtXkrkgD6t_eH12.
[9]	刘方蕾, 胥国毅, 王凡, 等. 基于差值计算法的系统分区惯量评估方法[J]. 电力系统自动化, 2020, 44(20): 46-53.
	LIU Fanglei, XU Guoyi, WANG Fan, et al. Assessment method of system partition inertia based on differential calculation method[J]. Automation of Electric Power Systems, 2020, 44(20): 46-53.
[10]	GILL S, STEPHEN B, GALLOWAY S. Wind turbine condition assessment through power curve copula modeling[J]. IEEE Transactions on Sustainable Energy, 2012, 3(1): 94-101. doi: 10.1109/TSTE.2011.2167164 URL
[11]	林顺富, 田二伟, 符杨, 等. 基于信息熵分段聚合近似和谱聚类的负荷分类方法[J]. 中国电机工程学报, 2017, 37(8): 2242-2253.
	LIN Shunfu, TIAN Erwei, FU Yang, et al. Power load classification method based on information entropy piecewise aggregate approximation and spectral clustering[J]. Proceedings of the Chinese Society for Electrical Engineering, 2017, 37(8): 2242-2253.
[12]	徐玉琴, 王莉莉, 张龙. 采用藤Copula构建风电场风速相依模型[J]. 电力系统及其自动化学报, 2015, 27(5): 62-66.
	XU Yuqin, WANG Lili, ZHANG Long. Modeling multiple wind speed dependency structure by vine-Copula in wind farm[J]. Proceedings of the Chinese Society of Universities for Electric Power System and Its Automation, 2015, 27(5): 62-66.
[13]	邓兆顺, 朱介北, 俞露杰, 等. 实现转子转速保护的双馈异步发电机有功输出速降新方案[J]. 电力系统保护与控制, 2021, 49(10): 113-122.
	DENG Zhaoshun, ZHU Jiebei, YU Lujie, et al. A novel fast active power output reduction scheme of a DFIG for rotor speed security[J]. Power System Protection and Control, 2021, 49(10): 113-122.

参数	取值
v_rat/(m·s^-1)	10
v_cut-in/(m·s^-1)	3
v_cut-out/(m·s^-1)	25
R/m	41

参数	取值
机组数量	33
额定功率/kW	1500
额定电压/V	575
惯性时间常数/s	5.04
发电机极对数	3

Copula函数	Kendall 系数	Speaman 系数	欧氏距离
Gumbel-Copula	0.9002	0.9849	0.0380
Clayton-Copula	0.7929	0.9371	0.1355
Frank-Copula	0.8882	0.9844	0.0423
经验Copula	0.8417	0.9546	0