
1.太原理工大学 电力系统运行与控制山西省重点实验室 煤电清洁控制教育部重点实验室,山西 太原 030024
2.中国长江三峡集团有限公司山西分公司,山西 太原 030024
朱志龙(1997 — ),男,博士研究生,主要研究方向为新能源装备建模以及电力系统稳定性分析与控制(E-mail:zhuzhilong1116@163.com);
秦文萍(1972 — ),女,教授,博士,通信作者,主要研究方向为新型电力系统稳定性和可靠性分析、微机保护、电力市场(E-mail:qinwenping@tyut.edu.cn)。
收稿日期:2024-09-05,
修回日期:2025-02-07,
网络出版日期:2025-07-07,
纸质出版日期:2025-09-10
移动端阅览
朱志龙,秦文萍,宋子宁等.基于两级注意力融合的DFIG并网电力系统暂态稳定评估[J].电力自动化设备,2025,45(09):79-87.
ZHU Zhilong,QIN Wenping,SONG Zining,et al.Transient stability assessment of DFIG grid-connected power system based on two-level attention fusion[J].Electric Power Automation Equipment,2025,45(09):79-87.
朱志龙,秦文萍,宋子宁等.基于两级注意力融合的DFIG并网电力系统暂态稳定评估[J].电力自动化设备,2025,45(09):79-87. DOI: 10.16081/j.epae.202507007.
ZHU Zhilong,QIN Wenping,SONG Zining,et al.Transient stability assessment of DFIG grid-connected power system based on two-level attention fusion[J].Electric Power Automation Equipment,2025,45(09):79-87. DOI: 10.16081/j.epae.202507007.
针对大规模双馈风电机组(DFIG)并网电力系统暂态稳定评估(TSA)中存在的动态时空特征挖掘不充分和无法兼顾不同尺度数据特征的问题,提出基于两级注意力融合(AF)的TSA方法。为了精确模拟DFIG并网电力系统的暂态稳定动态响应并兼顾仿真准确性和快速性,建立DFIG并网机电-电磁暂态混合仿真模型;为了充分挖掘暂态稳定特征,提出基于概率权重因子的特征融合方法,基于Transformer编码器提出两级AF模型,实现暂态稳定数据时空特征融合以及不同暂态尺度数据特征通道间权重值共享及融合。IEEE 10机39节点系统的仿真结果表明:所提模型的评估效果优于其他常用深度学习算法且具备良好的可解释性。
Aiming at the problems of insufficient mining of dynamic spatiotemporal features and inability to take the characteristics of data at different scales into account in the transient stability assessment(TSA) of large-scale doubly fed induction generator(DFIG) grid-connected power system,a TSA method based on two-level attention fusion(AF) is proposed. In order to accurately simulate the transient stability dynamic response of DFIG grid-connected power system and take both simulation accuracy and speed into account,a hybrid electromechanical-electromagnetic transient simulation model of DFIG grid-connected system is established. In order to fully explore the transient stability features,a feature fusion method based on probability weight factor is proposed. A two-level AF model based on Transformer encoder is proposed to achieve the fusion of spatiotemporal features of transient stability data and the sharing and fusion of weight values among feature channels of data with different transient scales. The simulative results of IEEE 10-machine 39-bus system show that the evaluation effect of the proposed model is superior to other commonly used deep learning algorithms and it has good interpretability.
范士雄 , 赵泽宁 , 郭剑波 , 等 . 数据驱动的电力系统暂态稳定评估方法综述 [J]. 中国电机工程学报 , 2024 , 44 ( 9 ): 3408 - 3428 .
FAN Shixiong , ZHAO Zening , GUO Jianbo , et al . Review on data-driven power system transient stability assessment technology [J]. Proceedings of the CSEE , 2024 , 44 ( 9 ): 3408 - 3428 .
刘明洋 , 潘文霞 , 李程昊 , 等 . 考虑撬棒和直流卸荷保护的双馈电机电磁暂态过程分析 [J]. 太阳能学报 , 2022 , 43 ( 7 ): 249 - 256 .
LIU Mingyang , PAN Wenxia , LI Chenghao , et al . Electromagnetic transient analysis of DFIG considering crowbar and chopper protection [J]. Acta Energiae Solaris Sinica , 2022 , 43 ( 7 ): 249 - 256 .
BEHDADNIA T , YASLAN Y , GENC I . A new method of deci-sion tree based transient stability assessment using hybrid simulation for real-time PMU measurements [J]. IET Gene-ration ,Transmission & Distribution, 2021 , 15 ( 4 ): 678 - 693 .
边晓燕 , 杨云轶 , 黄阮明 , 等 . 基于机电-电磁混合仿真的交直流混联受端电网连锁故障筛选指标及搜索策略 [J]. 中国电机工程学报 , 2023 , 43 ( 17 ): 6614 - 6628 .
BIAN Xiaoyan , YANG Yunyi , HUANG Ruanming , et al . Scree-ning indices and search strategy for AC-DC hybrid receiving-end power grid cascading failures based on hybrid electro-mechanical-electromagnetic simulation [J]. Proceedings of the CSEE , 2023 , 43 ( 17 ): 6614 - 6628 .
YI J , LIN W F , HU J X , et al . An integrated model-driven and data-driven method for on-line prediction of transient stability of power system with wind power generation [J]. IEEE Access , 2020 , 8 : 83472 - 83482 .
赵冬梅 , 谢家康 , 杜泽航 , 等 . 基于统计信息系数和Wasserstein生成对抗网络的风火系统暂态特征选择与两阶段稳定评估 [J]. 电力自动化设备 , 2023 , 43 ( 4 ): 106 - 113 .
ZHAO Dongmei , XIE Jiakang , DU Zehang , et al . Transient feature selection and two-stage stability assessment of wind-fire system based on uniform information coefficient and Wassers-tein-generative adversarial network [J]. Electric Power Automation Equipment , 2023 , 43 ( 4 ): 106 - 113 .
徐海亮 , 李志 , 王中行 . 低电压穿越期间双馈风电机组稳定性分析与电流分配方法 [J]. 电力自动化设备 , 2022 , 42 ( 8 ): 198 - 205 .
XU Hailiang , LI Zhi , WANG Zhongxing . Stability analysis and current distribution method of DFIG during low voltage ride-through [J]. Electric Power Automation Equipment , 2022 , 42 ( 8 ): 198 - 205 .
YIN L F , GE W . Mobileception-ResNet for transient stability prediction of novel power systems [J]. Energy , 2024 , 309 : 133163 .
LI B Q , WU J Y , HAO L L , et al . Anti-jitter and refined power system transient stability assessment based on long-short term memory network [J]. IEEE Access , 2020 , 8 : 35231 - 35244 .
高发骏 , 王怀远 , 党然 . 基于Transformer的暂态稳定评估模型的可解释性分析与模型更新研究 [J]. 电力系统保护与控制 , 2023 , 51 ( 17 ): 15 - 25 .
GAO Fajun , WANG Huaiyuan , DANG Ran . Interpretability ana-lysis and model update research of a transient stability assessment model based on Transformer [J]. Power System Protection and Control , 2023 , 51 ( 17 ): 15 - 25 .
LIN X , GOLE A M , YU M . A wide-band multi-port system equivalent for real-time digital power system simulators [J]. IEEE Transactions on Power Systems , 2009 , 24 ( 1 ): 237 - 249 .
崔树银 , 汪昕杰 . 基于最大信息系数和多目标Stacking集成学习的综合能源系统多元负荷预测 [J]. 电力自动化设备 , 2022 , 42 ( 5 ): 32 - 39,81 .
CUI Shuyin , WANG Xinjie . Multivariate load forecasting in integrated energy system based on maximal information coefficient and multi-objective Stacking ensemble learning [J]. Electric Power Automation Equipment , 2022 , 42 ( 5 ): 32 - 39,81 .
周生存 , 罗毅 , 易煊承 , 等 . 基于边界强化混合采样的两阶段电力系统暂态稳定评估 [J]. 电力自动化设备 , 2024 , 44 ( 4 ): 143 - 150 .
ZHOU Shengcun , LUO Yi , YI Xuancheng , et al . Two-stage tran-sient stability assessment of power system based on boundary enhanced hybrid sampling [J]. Electric Power Automation Equipment , 2024 , 44 ( 4 ): 143 - 150 .
CHEN Q F , LIN N , BU S Q , et al . Interpretable time-adaptive transient stability assessment based on dual-stage attention mechanism [J]. IEEE Transactions on Power Systems , 2023 , 38 ( 3 ): 2776 - 2790 .
曾令康 , 姚伟 , 艾小猛 , 等 . 基于双Q学习的考虑暂态稳定约束的电网薄弱线路辨识 [J]. 中国电机工程学报 , 2020 , 40 ( 8 ): 2429 - 2441 .
ZENG Lingkang , YAO Wei , AI Xiaomeng , et al . Double Q-learning based identification of weak lines in power grid considering transient stability constraints [J] . Proceedings of the CSEE , 2020 , 40 ( 8 ): 2429 - 2441 .
CLARK K , MILLER N W , SANCHEZ-GASCA J J . Modeling of GE wind turbine-generators for grid studies [J]. GE Energy , 2010 , 4 : 885 - 895 .
0
浏览量
0
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621