| 引用本文: | 左佳鑫,杨 秀,赵晓莉,等.考虑LVRT功率特性的直驱永磁风电场多机聚合辨识等值建模方法[J].电力系统保护与控制,2025,53(02):14-26.[点击复制] |
| ZUO Jiaxin,YANG Xiu,ZHAO Xiaoli,et al.Equivalence modeling method for multi-machine aggregation identification of direct-drive permanent magnet wind farm considering LVRT power characteristics[J].Power System Protection and Control,2025,53(02):14-26[点击复制] |
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| 摘要: |
| 针对故障情景下风电场等值模型精度偏低的问题，提出了一种考虑低压穿越(low voltage ride through, LVRT)功率特性的风电场多机聚合辨识等值建模方法。首先，基于风电机组LVRT期间有功功率动态特性的典型差异对风电场进行初次分群。其次，采用基于动态时间规整(dynamic time warping, DTW)度量的多路谱聚类(Ng-Jordan- Weiss, NJW)算法实现机群的二次划分，得到最终两阶段分群结果。然后，针对聚合所得的风电场多机等值模型，采用参数灵敏度分析方法来确定需要优化的重点参数，以各参数聚合值为初值，同时结合单机分步辨识、多机依次辨识以及等值阻抗辨识3种策略，实现风电场整体等值参数的优化。最后，对比了不同方法的拟合曲线及等值误差，结果表明所提方法有效提高了等值模型的精确性与适应性。 |
| 关键词: 直驱永磁风电场 低压穿越 分群聚类 多机等值 参数辨识 |
| DOI：10.19783/j.cnki.pspc.240595 |
| 投稿时间：2024-05-14修订日期：2024-11-28 |
| 基金项目:国家自然科学基金项目资助(52177098) |
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| Equivalence modeling method for multi-machine aggregation identification of direct-drive permanent magnet wind farm considering LVRT power characteristics |
| ZUO Jiaxin1,YANG Xiu1,ZHAO Xiaoli1,XIONG Xuejun2,ZHANG Yajun2,FENG Yuyao2 |
| (1. School of Electric Power Engineering, Shanghai University of Electric Power, Shanghai 200090, China;
2. State Grid Shanghai Electric Power Research Institute, Shanghai 200437, China) |
| Abstract: |
| Aiming at the problem of low accuracy of wind farm equivalent models under fault scenarios, a multi-machine aggregation identification equivalence modeling method for wind farm considering low voltage ride through (LVRT) power characteristics is proposed. Firstly, the wind farm is initially grouped based on the typical differences in active power dynamic characteristics during LVRT of wind turbines. Secondly, the Ng-Jordan-Weiss (NJW) algorithm based on dynamic time warping (DTW) metric is used to realize the secondary division of the cluster, and the final two-stage clustering results are obtained. Then, for the aggregated multi-machine equivalent model of the wind farm, parameter sensitivity analysis is used to determine the key parameters to be optimized. The aggregated values of each parameter are taken as the initial values, and the overall equivalent parameters of the wind farm are optimized using the three strategies of single-machine step-by-step identification, multi-machine sequential identification, and equivalent impedance identification. Finally, the fitting curves and equivalent errors of different methods are compared, and the results show that the proposed method effectively improves the accuracy and adaptability of the equivalent model. |
| Key words: direct-drive permanent magnet wind farm LVRT grouping and clustering multi-machine equivalence parameter identification |
