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Measurement-based cell-DT method for power system transient stability classification

机译:电力系统暂态稳定分类的基于测量的单元DT算法

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In this paper, a combined Characteristic Ellipsoid (CELL) and Decision Tree (DT) method for fast classifying the transient stability of power systems after a large disturbance is proposed. The proposed two-stage method involves projection of the PMU measurement data after the disturbance on a multidimensional space to form the CELL and then classification of the transient stability using DT which takes the characteristic attributes of CELL under different fault scenarios as input features. The dynamic behaviors after a disturbance for both stable and unstable situations are identified from the variation of the CELL's shape. The database, composed of the geometrical properties of the CELL such as volume, eccentricity, center and change rate of volume, is used to train a DT for transient stability classification. Case study on a IEEE 39-bus system demonstrates the feasibility of the proposed method. Investigations show that the proposed method requires less information from the system to fast classify the transient stability with high precision.
机译:提出了一种结合特征椭球(CELL)和决策树(DT)的方法对大扰动后的电力系统暂态稳定进行快速分类。提出的两阶段方法涉及将扰动后的PMU测量数据投影到多维空间上以形成CELL,然后使用DT分类暂态稳定性,该DT将不同故障情况下CELL的特征属性作为输入特征。根据CELL形状的变化,可以确定扰动后稳定和不稳定情况下的动态行为。由CELL的几何特性(例如体积,偏心率,中心和体积变化率)组成的数据库用于训练DT,以进行暂态稳定性分类。在IEEE 39总线系统上的案例研究证明了该方法的可行性。研究表明,所提出的方法需要较少的系统信息即可对瞬态稳定性进行高精度分类。

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