Probability Eigenvalue Sensitivity Indices for Determining Optimal Access Points of Wind Farms

doi:10.12204/j.issn.1000-7229.2021.10.013

Abstract

Abstract:

With the ever-increasing penetration of wind power in an interconnected power system, the power flow distribution is becoming more and more complicated and uncertain. To analyze the stable operating characteristics of an interconnected power system with wind power integrated and enhance the accommodation capability for intermittent renewable generation, this paper applies probabilistic eigenvalue sensitivity indices to determine optimal access points of wind farms. Under multiple operation conditions of an interconnected power system, the relationship between the system state matrix and the residual index is studied, the probability sensitivity indices are developed, and the correlation factors and strongly related units that cause the low-frequency oscillation of the system are identified. The eigenvalue analysis method and dynamic time-domain simulation are used to analyze and compare the influences of “adding” and “replacing” wind power configuration schemes on the system oscillation characteristics, and to determine the optimal access points of wind farms. Finally, two numerical examples are employed to demonstrate the feasibility and efficiency of the proposed approach.

Key words: interconnected power system, probabilistic sensitivity, eigenvalue analysis, small-signal stability, wind farm, access point

CLC Number:

TM74

HE Ping, LIU Dongzhe, WEN Fushuan, FANG Qiyuan, ZHENG Mingming, LI Zhao. Probability Eigenvalue Sensitivity Indices for Determining Optimal Access Points of Wind Farms[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(10): 119-128.

Figures/Tables 19

Fig.1 Probability distribution of real part of the eigenvalues

Fig.2 Desired eigenvalue distribution region

Fig.3 The WSCC 3-machine 9-bus system

Table 1 PSIs corresponding to different input signals

Fig.4 Probability distribution of eigenvalues

Table 2 PSIs of α ' k and ξ ' k corresponding to different input signals

Fig.5 Structure of a DFIG

Table 3 Parameters of PSSs

Fig.6 Power system with “addition” or “replacement” of a wind farm

Fig.7 Damping ratio changes for two oscillation modes with DFIG output increased

Table 4 Electro-mechanical oscillatory modes under different operating conditions

Table 5 Partial results of eigenvalues analysis under various DFIG outputs (DFIG at Bus 3)

Table 6 Electro-mechanical oscillatory modes under various DFIG outputs (DFIG at Bus 2)

Fig.8 Response curves under different schemes

Table 7 Partial results of eigenvalues analysis under different scenarios (DFIG at Bus 3)

Fig.9 Active power response curves of G1 under different scenarios

Table 8 PSIs of the damping ratios corresponding to power signal under different operating conditions

Table 9 The SCG corresponding to different modes with its H m a x P S I

Table 10 Electro-mechanical modes for the system with DFIG connected to different PCC buses

References 23

[1]	国际太阳能光伏网. 预计到2050年全球风电和光伏发电量占比50%[EB/OL]. (2019-04-01) [2020-12-06]. http://solor.in-en.com/html/solar-2335339.shtml.
[2]	前瞻产业研究院. 全球风电行业发展前景分析海上风电是欧洲市场亮点[EB/OL]. (2018-02-08) [2020-12-06]. https://bg.qianzhan.com/report/detail/300/180208-b7de55ef.html.
[3]	王一凡, 赵成勇, 郭春义. 直驱风电场与柔直互联系统的传递函数模型及其低频振荡稳定性分析[J]. 中国电机工程学报, 2020, 40(5): 1485-1498.
	WANG Yifan, ZHAO Chengyong, GUO Chunyi. Transfer function model and low-frequency stability analysis for PMSG-based wind farm interconnected with flexible-HVDC system[J]. Proceedings of the CSEE, 2020, 40(5): 1485-1498.
[4]	KUMAR D, CHATTERJEE K. Analysis and enhancement of small-signal stability on DFIG-based wind integrated power system through the optimal design of linear quadratic regulator[J]. IET Renewable Power Generation, 2020, 14(4): 628-639. doi: 10.1049/iet-rpg.2018.6095 URL
[5]	和萍, 文福拴, 薛禹胜, 等. 风电场并网对互联系统小干扰稳定及低频振荡特性的影响[J]. 电力系统自动化, 2014, 38(22): 1-10.
	HE Ping, WEN Fushuan, XUE Yusheng, et al. Impacts of wind power integration on small signal stability and low frequency oscillation characteristics of interconnected power systems[J]. Automation of Electric Power Systems, 2014, 38(22): 1-10.
[6]	杨悦. 含大规模风电并网的互联电力系统低频振荡特性分析与控制研究[D]. 北京: 华北电力大学, 2018.
	YANG Yue. Analysis and control research on low frequency oscillation of large-scale wind power grid in power system[D]. Beijing: North China Electric Power University, 2018.
[7]	董文凯, 杜文娟, 王海风. 用于振荡稳定性分析的并网风电场动态等效模型[J]. 中国电机工程学报, 2021, 41(1): 75-87.
	DONG Wenkai, DU Wenjuan, WANG Haifeng. Dynamic equivalent model of a grid-connected wind farm for oscillation stability analysis[J]. Proceedings of the CSEE, 2021, 41(1): 75-87.
[8]	HE P, WEN F S, LEDWICH G, et al. An investigation on interarea mode oscillations of interconnected power systems with integrated wind farms[J]. International Journal of Electrical Power & Energy Systems, 2016, 78: 148-157. doi: 10.1016/j.ijepes.2015.11.052 URL
[9]	GAUTAM D, VITTAL V, HARBOUR T. Impact of increased penetration of DFIG-based wind turbine generators on transient and small signal stability of power systems[J]. IEEE Transactions on Power Systems, 2009, 24(3): 1426-1434. doi: 10.1109/TPWRS.2009.2021234 URL
[10]	王洋, 杜文娟, 王海风. 多风电场-多机电力系统次同步振荡稳定性分析[J]. 中国电机工程学报, 2019, 39(22): 6562-6572.
	WANG Yang, DU Wenjuan, WANG Haifeng. Stability analysis of subsynchronous oscillation in multi-machine power system with multiple wind farms[J]. Proceedings of the CSEE, 2019, 39(22): 6562-6572.
[11]	李生虎, 张维, 汪秀龙. 基于系统有功网损-风速灵敏度的双馈机风电场并网位置研究[J]. 电力建设, 2015, 36(4): 8-15.
	LI Shenghu, ZHANG Wei, WANG Xiulong. Integration point of doubly-fed induction generator wind farm based on active power loss and wind speed sensitivity[J]. Electric Power Construction, 2015, 36(4): 8-15.
[12]	LI W N, WANG Q. Stochastic production simulation for generating capacity reliability evaluation in power systems with high renewable penetration[J]. Energy Conversion and Economics, 2020, 1(3): 210-220. doi: 10.1049/enc2.12016 URL
[13]	马闻达, 王西田, 解大. 大规模风电场并网系统次同步振荡功率传播特性研究[J]. 中国电机工程学报, 2020, 40(16): 5217-5229.
	MA Wenda, WANG Xitian, XIE Da. Characteristics of subsynchronous oscillation power propagation in the large-scale wind farm integrated system[J]. Proceedings of the CSEE, 2020, 40(16): 5217-5229.
[14]	SAHOO B, ROUTRAY S K, ROUT P K. Execution of advanced solar-shunt active filter for renewable power application[J]. Energy Conversion and Economics, 2021, 2(2): 100-118. doi: 10.1049/enc2.12032 URL
[15]	王钊, 王勃, 冯双磊, 等. 区域多风电场功率的分位数回归概率预测方法[J]. 电网技术, 2020, 44(4): 1368-1375.
	WANG Zhao, WANG Bo, FENG Shuanglei, et al. Probabilistic forecasts based on quantile regression for regional wind farms[J]. Power System Technology, 2020, 44(4): 1368-1375.
[16]	DU W J, BI J T, CAO J, et al. A method to examine the impact of grid connection of the DFIGs on power system electromechanical oscillation modes[J]. IEEE Transactions on Power Systems, 2016, 31(5): 3775-3784. doi: 10.1109/TPWRS.2015.2494082 URL
[17]	周彦彤, 郝丽丽, 王昊昊, 等. 大容量风电场柔直并网系统的送/受端次同步振荡分析与抑制[J]. 电力自动化设备, 2020, 40(3): 100-106.
	ZHOU Yantong, HAO Lili, WANG Haohao, et al. Analysis and suppression of SSO at sending/receiving end in VSC-HVDC system connected large-capacity wind farms[J]. Electric Power Automation Equipment, 2020, 40(3): 100-106.
[18]	MITRA A, CHATTERJEE D. A new sensitivity based approach to study impact of wind power penetration on transient stability[C]// 2012 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES)2012. Bengaluru, India: IEEE, 2012: 1-6.
[19]	王忱, 石立宝, 姚良忠, 等. 大规模双馈型风电场的小扰动稳定分析[J]. 中国电机工程学报, 2010, 30(4): 63-70.
	WANG Chen, SHI Libao, YAO Liangzhong, et al. Small signal stability analysis of the large-scale wind farm with DFIGs[J]. Proceedings of the CSEE, 2010, 30(4): 63-70.
[20]	王克文, 谢志棠, 史述红, 等. 基于概率特征根分析的电力系统稳定器参数设计[J]. 电力系统自动化, 2001, 25(11): 20-23.
	WANG Kewen, TSE C T, SHI Shuhong, et al. Power system stabilizer (PSS) parameter design based on probabilistic eigenvalue analysis[J]. Automation of Electric Power Systems, 2001, 25(11): 20-23.
[21]	李生虎, 齐涛, 张楠, 等. DFIG风电场经交流/柔性直流并网系统最优潮流与灵敏度分析[J]. 电力自动化设备, 2020, 40(7): 46-57.
	LI Shenghu, QI Tao, ZHANG Nan, et al. Optimal power flow and sensitivity analysis for power system with DFIG-wind farms integrated through AC/VSC-HVDC power transmission[J]. Electric Power Automation Equipment, 2020, 40(7): 46-57.
[22]	CHUNG C Y, WANG K W, TSE C T, et al. Probabilistic eigenvalue sensitivity analysis and PSS design in multimachine systems[J]. IEEE Transactions on Power Systems, 2003, 18(4): 1439-1445. doi: 10.1109/TPWRS.2003.818709 URL
[23]	PAGOLA F L, PEREZ-ARRIAGA I J, VERGHESE G C. On sensitivities, residues and participations: Applications to oscillatory stability analysis and control[J]. IEEE Transactions on Power Systems, 1989, 4(1): 278-285. doi: 10.1109/59.32489 URL