Liu Ge, Liu Jun, Liu Andong
College of Automation, Xi'an University of Technology, Xi'an, 710048, China.
Xi'an Aero-Engine Controls Technology Co., Ltd, Xi'an, 710072, China.
Sci Rep. 2024 Sep 27;14(1):22290. doi: 10.1038/s41598-024-73505-6.
In the power system, the wind farm based on Doubly-Fed Induction Generator (DFIG) may lead to Subsynchronous Oscillation (SSO), which poses a challenge to the stability of the power grid. In order to accurately evaluate SSO, this paper proposes a new evaluation method. It is divided into two main stages: firstly, the interference level of Phasor Measurement Unit (PMU) data is identified by using the classification model based on Upper Confidence Bound (UCB) and Double Deep Q Network (DDQN). Then, an SSO parameter estimation model based on Local Feature Fusion Transformer (LFF-Transformer) network is designed for data with different interference levels. Experimental results show that the errors of eRMSE-f and EMAPE-F are 0.001 and 0.003 respectively, and the errors of eRMSE-δ and EMAPE-δ are 0.009 and 0.015 respectively. In terms of training and testing time, this method is 90 s and 18 s respectively, which is significantly better than Multi-SVR and Multi-CNN. After application, the frequency deviation decreased from 0.05 to 0.02 Hz, the voltage deviation decreased from 3.5 to 1.5%, the power fluctuation decreased from 10 to 5 MW, the SSO frequency decreased from 1.5 Hz to less than 0.5 Hz, and the SSO damping ratio increased from 0.08 to 0.15. This shows that the proposed method effectively increases the stability of the power grid.
在电力系统中，基于双馈感应发电机（DFIG）的风电场可能会导致次同步振荡（SSO），这对电网的稳定性构成了挑战。为了准确评估次同步振荡，本文提出了一种新的评估方法。它分为两个主要阶段：首先，使用基于上置信界（UCB）和双深度Q网络（DDQN）的分类模型来识别相量测量单元（PMU）数据的干扰水平。然后，针对不同干扰水平的数据设计了一种基于局部特征融合变压器（LFF-Transformer）网络的次同步振荡参数估计模型。实验结果表明，eRMSE-f和EMAPE-F的误差分别为0.001和0.003，eRMSE-δ和EMAPE-δ的误差分别为0.009和0.015。在训练和测试时间方面，该方法分别为90秒和18秒，明显优于多支持向量回归（Multi-SVR）和多卷积神经网络（Multi-CNN）。应用后，频率偏差从0.05降至0.02赫兹，电压偏差从3.5%降至1.5%，功率波动从10兆瓦降至5兆瓦，次同步振荡频率从1.5赫兹降至小于0.5赫兹，次同步振荡阻尼比从0.08增至0.15。这表明所提出的方法有效地提高了电网的稳定性。
