保持主导振荡模态的双馈风电场动态聚合等值方法

王渝红; 杜婷; 廖建权; 宋雨妍; 朱玲俐

doi:10.19912/j.0254-0096.tynxb.2023-0164

PDF(3046 KB)

太阳能学报 ›› 2024, Vol. 45 ›› Issue (6) : 518-529. DOI: 10.19912/j.0254-0096.tynxb.2023-0164

保持主导振荡模态的双馈风电场动态聚合等值方法

王渝红, 杜婷, 廖建权, 宋雨妍, 朱玲俐

作者信息 +

DYNAMIC AGGREGATION EQUIVALENCE METHOD FOR DFIG-BASED WIND FARM WITH MAINTAINED DOMINANT OSCILLATION MODE

Wang Yuhong, Du Ting, Liao Jianquan, Song Yuyan, Zhu Lingli

Author information +

文章历史 +

摘要

针对风电场详细建模出现的“维数灾”问题,计及双馈风电机组各控制环节与系统振荡模态的关系,以保持等值前后主导振荡模态一致为目标,提出考虑风电机组多时间尺度级联特性的风电场站等值聚合方法。首先考虑风电机组多控制环节级联建立风电场状态空间模型;其次,利用振荡能量级判别系统主导振荡模态,并基于参与因子分析不同模态的关键影响因素;在此基础上,以主导振荡模态的关键影响因素为分群指标,结合自编码器进行数据降维处理,经改进聚合算法聚类和拓扑变换获取等值参数等环节后得到等值模型。最后,在Matlab平台分别搭建单机模型和含24台双馈风电机组的风电场模型,验证了所提等值方法的有效性。

Abstract

In order to solve the problem of "dimensional disaster" in the detailed modeling of wind farms, this paper considers the relationship between each control link of the doubly-fed wind turbine and the system oscillation mode, by which the goal is to keep the dominant oscillation mode consistent before and after the equivalent value. For this reason, an equivalent aggregation method for wind farms considering the multi-time scale cascade characteristics of wind turbines is proposed. Firstly, this paper takes into account the cascade of multiple control links of wind turbines to establish a state space model of wind farms. Secondly, use the oscillation energy level to identify the dominant oscillation mode of the system. Analyze the key influencing factors affecting different modes with participation factor. Then, the key influencing factor of the dominant oscillation mode is taken as the clustering index, and data dimensionality reduction is performed in combination with auto-encoder. The equivalent model is obtained after improving aggregation algorithm clustering and topological transformation to obtain equivalent parameters. Finally, a single-machine model and a wind farm model with 24 doubly-fed wind turbines are built in Matlab to verify the validity of the equivalent method proposed in this paper.

导出引用

王渝红, 杜婷, 廖建权, 宋雨妍, 朱玲俐. 保持主导振荡模态的双馈风电场动态聚合等值方法[J]. 太阳能学报. 2024, 45(6): 518-529 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0164

Wang Yuhong, Du Ting, Liao Jianquan, Song Yuyan, Zhu Lingli. DYNAMIC AGGREGATION EQUIVALENCE METHOD FOR DFIG-BASED WIND FARM WITH MAINTAINED DOMINANT OSCILLATION MODE[J]. Acta Energiae Solaris Sinica. 2024, 45(6): 518-529 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0164

中图分类号： TM614

参考文献

[1] 马静, 沈雅琦, 杜延菱, 等. 适应宽频振荡的风电并网系统主动阻尼技术综述[J]. 电网技术, 2021, 45(5): 1673-1686.
MA J, SHEN Y Q, DU Y L, et al.Overview on active damping technology of wind power integrated system adapting to broadband oscillation[J]. Power system technology, 2021, 45(5): 1673-1686.
[2] CHENG Y Z, FAN L L, ROSE J, et al.Real-world subsynchronous oscillation events in power grids with high penetrations of inverter-based resources[J]. IEEE transactions on power systems, 2023, 38(1): 316-330.
[3] 占颖, 谢小荣, 柴炜, 等. 风电次/超同步振荡的安全域分析[J]. 中国电机工程学报, 2022, 42(23): 8446-8454.
ZHAN Y, XIE X R, CHAI W, et al.Analyzing the security region of sub/super-synchronous oscillation in wind power integrated systems[J]. Proceedings of the CSEE, 2022, 42(23): 8446-8454.
[4] 何君毅, 周瑀涵, 王康, 等. 主导模态保持的风电场站自适应等值方法[J]. 电力系统自动化, 2021, 45(11): 28-36.
HE J Y, ZHOU Y H, WANG K, et al.Self-adaptive equivalence method for wind farm with maintained dominant mode[J]. Automation of electric power systems, 2021, 45(11): 28-36.
[5] 薛翼程, 张哲任, 徐政. 适用于短路故障分析的风电场动态等值建模方法[J]. 太阳能学报, 2022, 43(5): 327-335.
XUE Y C, ZHANG Z R, XU Z.Dynamic equivalent model of wind farm for short-circuit faults analysis[J]. Acta energiae solaris sinica, 2022, 43(5): 327-335.
[6] ZHOU Y H, ZHAO L, LEE W J.Robustness analysis of dynamic equivalent model of DFIG wind farm for stability study[J]. IEEE transactions on industry applications, 2018, 54(6): 5682-5690.
[7] 陈晨. 并网DFIG风电场引发电力系统次同步振荡开环模式谐振机理[D]. 北京: 华北电力大学, 2019.
CHEN C.The open-loop modal resonance mechanism of SSOs in power systems induced by grid-connected DFIG wind farms[D]. Beijing: North China Electric Power University, 2019.
[8] 朱林, 陈达, 张健, 等. 计及特征约束的南方电网主网架动态等值方案[J]. 电力自动化设备, 2019, 39(9): 206-212.
ZHU L, CHEN D, ZHANG J, et al.Dynamic equivalent scheme for main grid of China southern power grid considering feature constraints[J]. Electric power automation equipment, 2019, 39(9): 206-212.
[9] 韩平平, 夏雨, 丁明, 等. 基于PCA和CA-ST方法的风电场等值建模研究[J]. 太阳能学报, 2020, 41(11): 267-277.
HAN P P, XIA Y, DING M, et al.Equivalent modeling of wind farm based on PCA and CA-ST methods[J]. Acta energiae solaris sinica, 2020, 41(11): 267-277.
[10] 吴磊, 晁璞璞, 李甘, 等. 数据-模型混合驱动的风电场聚合等值建模方法[J]. 电力系统自动化, 2022, 46(15): 66-74.
WU L, CHAO P P, LI G, et al.Hybrid data-model-driven aggregation equivalent modeling method for wind farm[J]. Automation of electric power systems, 2022, 46(15): 66-74.
[11] ZHOU Y H, ZHAO L, MATSUO I B M, et al. A dynamic weighted aggregation equivalent modeling approach for the DFIG wind farm considering the Weibull distribution for fault analysis[J]. IEEE transactions on industry applications, 2019, 55(6): 5514-5523.
[12] 周瑀涵, 王冠中, 王康, 等. 用于风电场小干扰稳定性分析的结构保持等值方法[J]. 电力系统自动化, 2021, 45(19): 133-140.
ZHOU Y H, WANG G Z, WANG K, et al.Structure-retained equivalent method for small signal stability analysis of wind farm[J]. Automation of electric power systems, 2021, 45(19): 133-140.
[13] 韩平平, 王欢, 王希, 等. 基于指标降维及集电系统辨识的双馈风电场次同步振荡等值[J]. 中国电机工程学报, 2022, 42(23): 8465-8475.
HAN P P, WANG H, WANG X, et al.Subsynchronous oscillation equivalence of doubly-fed wind farms based on index dimension reduction and collector system identification[J]. Proceedings of the CSEE, 2022, 42(23): 8465-8475.
[14] 王玉鹏, 严干贵, 穆钢, 等. 交流电流控制尺度下的并网VSC聚合建模研究[J]. 中国电机工程学报, 2022, 42(8): 2900-2910.
WANG Y P, YAN G G, MU G, et al.Research on aggregation modeling of grid connected VSC under AC current control scale[J]. Proceedings of the CSEE, 2022, 42(8): 2900-2910.
[15] 胡家兵, 袁小明, 程时杰. 电力电子并网装备多尺度切换控制与电力电子化电力系统多尺度暂态问题[J]. 中国电机工程学报, 2019, 39(18): 5457-5467, 5594.
HU J B, YUAN X M, CHENG S J.Multi-time scale transients in power-electronized power systems considering multi-time scale switching control schemes of power electronics apparatus[J]. Proceedings of the CSEE, 2019, 39(18): 5457-5467, 5594.
[16] HU J B, YUAN H, YUAN X M.Modeling of DFIG-based WTs for small-signal stability analysis in DVC timescale in power electronized power systems[J]. IEEE transactions on energy conversion, 2017, 32(3): 1151-1165.
[17] YUAN H, YUAN X M, HU J B.Modeling of grid-connected VSCs for power system small-signal stability analysis in DC-link voltage control timescale[J]. IEEE transactions on power systems, 2017, 32(5): 3981-3991.
[18] 尚磊, 董旭柱, 刘超. 惯量-刚度补偿器增强接入弱电网风电场直流电压时间尺度小干扰稳定的作用机理分析[J]. 中国电机工程学报, 2021, 41(7): 2321-2331.
SHANG L, DONG X Z, LIU C.Mechanism analysis of stability improvement of wind farm connected into weak grid by inertia-stiffness compensator in DC-link voltage time scale[J]. Proceedings of the CSEE, 2021, 41(7): 2321-2331.
[19] 饶环宇. 考虑锁相环动态过程的双馈风机电流控制时间尺度小扰动模型[D]. 武汉: 华中科技大学, 2019.
RAO H Y.Modeling of doubly fed induction generator type wind turbine on current control-time scale when considering the dynamic of phase locked loop[D]. Wuhan: Huazhong University of Science and Technology, 2019.
[20] 韩平平, 王欢, 王希, 等. 基于主导变量阻尼控制的双馈风电场次同步振荡抑制[J]. 电力系统及其自动化学报, 2022, 34(1): 26-37, 75.
HAN P P, WANG H, WANG X, et al.Sub-synchronous oscillation suppression for doubly-fed wind farm based on dominant variable damping control[J]. Proceedings of the CSU-EPSA, 2022, 34(1): 26-37, 75.
[21] 刘巨, 姚伟, 文劲宇. 考虑PLL和接入电网强度影响的双馈风机小干扰稳定性分析与控制[J]. 中国电机工程学报, 2017, 37(11): 3162-3173, 3371.
LIU J, YAO W, WEN J Y.Small signal stability analysis and control of double-fed induction generator considering influence of PLL and power grid strength[J]. Proceedings of the CSEE, 2017, 37(11): 3162-3173, 3371.
[22] 王鹏, 刘天琪, 王顺亮, 等. 水电机组超低频振荡小信号模型及影响因素分析[J]. 中国电机工程学报, 2020, 40(18): 5942-5955.
WANG P, LIU T Q, WANG S L, et al.Small-signal model and influencing factors analysis of ultra-low frequency oscillation in hydropower unit[J]. Proceedings of the CSEE, 2020, 40(18): 5942-5955.
[23] YU J B, ZHOU X K.One-dimensional residual convolutional autoencoder based feature learning for gearbox fault diagnosis[J]. IEEE transactions on industrial informatics, 2020, 16(10): 6347-6358.
[24] 刘家瑞, 杨国田, 杨锡运. 基于深度卷积自编码器的风电机组故障预警方法研究[J]. 太阳能学报, 2022, 43(11): 215-223.
LIU J R, YANG G T, YANG X Y.Research on wind turbine fault warning method based on deep convolution auto-encoder[J]. Acta energiae solaris sinica, 2022, 43(11): 215-223.
[25] 黄佳欢, 余建波. 基于形态帽积卷积自编码器模型的齿轮箱故障诊断[J]. 机械工程学报, 2023, 59(23): 132-145.
HUANG J H, YU J B.Gearbox fault diagnosis research based on morphological hat product convolutional autoencoder[J]. Journal of mechanical engineering, 2023, 59(23): 132-145.
[26] 袁非牛, 章琳, 史劲亭, 等. 自编码神经网络理论及应用综述[J]. 计算机学报, 2019, 42(1): 203-230.
YUAN F N, ZHANG L, SHI J T, et al.Theories and applications of auto-encoder neural networks: a literature survey[J]. Chinese journal of computers, 2019, 42(1): 203-230.
[27] RIFAI S, VINCENT P, MULLER X, et al.Contractive auto-encoders: explicit invariance during feature extraction[C]//Proceedings of the 28th International Conference on International Conference on Machine Learning, Bellevue, Washington, USA, 2011: 833-840.
[28] 马宏忠, 严岩. 基于混沌理论和GOA-K-means算法的有载分接开关状态特征分析计算方法[J]. 电工技术学报, 2021, 36(7): 1399-1406.
MA H Z, YAN Y.Analysis and calculation method of on-load tap changers state characteristics based on chaos theory and grasshopper optimization algorithm-K-means algorithm[J]. Transactions of China Electrotechnical Society, 2021, 36(7): 1399-1406.
[29] 张永新, 李飞, 张榴晨, 等. 基于线路阻抗聚类的分布式光伏电站等效建模[J]. 太阳能学报, 2022, 43(5): 312-318.
ZHANG Y X, LI F, ZHANG L C, et al.Equivalent modeling of distributed photovoltaic power stations based on line impedance clustering[J]. Acta energiae solaris sinica, 2022, 43(5): 312-318.
[30] 朱廷猛, 孙海顺, 秦世耀, 等. 弱电网下双馈风机并网系统的次同步振荡研究[J]. 电网技术, 2021, 45(5): 1641-1648.
ZHU T M, SUN H S, QIN S Y, et al.Sub-synchronous oscillation in DFIG system connected to weak grid[J]. Power system technology, 2021, 45(5): 1641-1648.