聂永辉, 曲铭锐, 周恒宇, 张瑞东, 张杰. 基于小脑模型-模糊滑模控制的电力系统低频振荡控制策略研究[J]. 电网技术, 2024, 48(2): 789-798. DOI: 10.13335/j.1000-3673.pst.2022.2345
引用本文: 聂永辉, 曲铭锐, 周恒宇, 张瑞东, 张杰. 基于小脑模型-模糊滑模控制的电力系统低频振荡控制策略研究[J]. 电网技术, 2024, 48(2): 789-798. DOI: 10.13335/j.1000-3673.pst.2022.2345
NIE Yonghui, QU Mingrui, ZHOU Hengyu, ZHANG Ruidong, ZHANG Jie. Control Strategy of Low-frequency Oscillation Suppression in Power System Based on CMAC-FSMC[J]. Power System Technology, 2024, 48(2): 789-798. DOI: 10.13335/j.1000-3673.pst.2022.2345
Citation: NIE Yonghui, QU Mingrui, ZHOU Hengyu, ZHANG Ruidong, ZHANG Jie. Control Strategy of Low-frequency Oscillation Suppression in Power System Based on CMAC-FSMC[J]. Power System Technology, 2024, 48(2): 789-798. DOI: 10.13335/j.1000-3673.pst.2022.2345

基于小脑模型-模糊滑模控制的电力系统低频振荡控制策略研究

Control Strategy of Low-frequency Oscillation Suppression in Power System Based on CMAC-FSMC

  • 摘要: 由于现代电力系统互联规模不断增大,柔性控制系统加入和长距离输电使得电网阻尼不断减小,运行方式的多变性不断改变系统潮流分布,极易引发低频振荡现象。针对此问题,该文提出一种基于小脑模型关节误差修正的模糊滑模附加阻尼控制策略。首先在模糊滑模控制(fuzzy sliding mode control,FSMC)的基础上,引入小脑模型关节控制(cerebellar model articulation control,CMAC)理论,构建CMAC-FSMC算法,提高滑模趋近阶段模糊逻辑对系统的补偿能力,最大程度提高系统稳定性能;其次通过构造CMAC-FSMC的调整指标与总控制率,减小控制误差,提高控制性能;最后通过线性降阶方法建立被控系统模型并确定区间振荡模态,采用几何测度法选择最佳反馈信号和安装位置,基于所提出的CMAC-FSMC方法进行广域阻尼控制器设计。通过对10机39节点系统进行仿真验证,结果表明CMAC-FSMC控制策略能够有效提高系统阻尼,显著抑制低频振荡。

     

    Abstract: Due to the increasing scale of interconnection of the modern power systems, the addition of flexible control systems and the long-distance transmission make the damping of power networks reduced continuously, and the variability of operation modes changes the distribution of power flows, which easily leads to low frequency oscillations. To solve this problem, a fuzzy sliding mode additional damping control strategy based on the joint error correction of the cerebellar model is presented. Firstly, on the basis of fuzzy sliding mode control (FSMC), the cerebellar model articulation control (CMAC) theory is introduced, and the CMAC-FSMC algorithm is constructed to improve the compensation ability of the fuzzy logic in the sliding mode approaching stage and maximize the system stability performance. Secondly, by constructing the adjustment index and the total control rate of the CMAC-FSMC, the control error is reduced and the control performance is improved. Finally, the model of the controlled system is established and the interval oscillation mode is determined by the linear descending method. The optimal feedback signal and the installation locations are selected by the geometric measure method. Based on the proposed CMAC-FSMC method, the wide area damping controller is designed. The simulation results of a ten-machine thirty-nine-node system show that the CMAC-FSMC control strategy is able to effectively improve the system damping and significantly suppress the low frequency oscillation.

     

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