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Support Vector Machine Based Transient Stability Identification in Distribution System with Distributed Generation

机译:分布式发电系统中基于支持向量机的暂态稳定辨识

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摘要

Due to the increased penetration of distributed generations in distribution systems, transient stability is one of the major concerns to be analyzed. This article presents a support vector machine based approach for transient stability detection using post-disturbance signals extracted from the optimally located distributed generations in a distribution system having distributed generation. Initially, distributed generations are placed optimally, and their optimal sizes are found with objectives of loss reduction and reliability improvement for various distributed generation penetration levels, system configurations, and system loading conditions. Various asymmetrical and symmetrical faults at different locations in the system are simulated to calculate the critical clearing times. The post-disturbance values of terminal voltage, active power, reactive power, and speed obtained from the distributed generations for both stable and unstable cases are used as input features of the support vector machine for finding the transient stability status. The dynamic simulations are carried out on IEEE 33-node and IEEE 69-node radial distribution test systems with four distributed generations, modeled in DIgSI-LENT power factory software (DIgSILENT GmbH, Germany). The proposed support vector machine based approach predicts the post-disturbance transient stability of the distribution system accurately.
机译:由于分布式系统在分布式系统中的渗透率不断提高,因此暂态稳定性是需要分析的主要问题之一。本文提出了一种基于支持向量机的方法,该方法使用从具有分布式发电的配电系统中最优定位的分布式发电中提取的扰动后信号来进行暂态稳定性检测。最初,将分布式发电优化放置,并找到其最佳尺寸,以减少各种分布式发电渗透水平,系统配置和系统负载条件的损失并提高可靠性。模拟了系统中不同位置的各种非对称和对称故障,以计算临界清除时间。从稳定和不稳定情况下的分布式发电获得的终端电压,有功功率,无功功率和速度的后扰动值被用作支持向量机的输入特征,用于找到暂态稳定状态。动态仿真是在具有33个分布式代的IEEE 33节点和IEEE 69节点径向分布测试系统上进行的,该系统以DIgSI-LENT电力工厂软件(德国DIgSILENT GmbH)为模型。所提出的基于支持向量机的方法可以准确预测配电系统的扰动后瞬态稳定性。

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