A Classification Approach Using Support Vector Machines to Prevent Distance Relay Maloperation Under Power Swing and Voltage Instability
A Classification Approach Using Support Vector Machines to Prevent Distance Relay Maloperation Under Power Swing and Voltage Instability
复制标题
利用支持向量机防止电网波动和电压不稳定情况下距离继电器误动作的分类方法
DOI：
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发表时间：
2012
影响因子：
4.4
通讯作者：
Suresh Chandra Srivastava
中科院分区：
文献类型：
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作者：
K. Seethalekshmi;Subaran Singh;Suresh Chandra Srivastava
在电力传输系统中，距离继电器在某些系统事件（如功率波动和电压不稳定）下容易发生误动作，导致视阻抗轨迹进入继电器的保护区域。快速、可靠地检测功率波动时发生的对称故障，对距离继电器的运行提出了另一个挑战。本文提出了一种新的基于支持向量机（svm）的分类保护方案，对传统距离继电器的运行进行监控。该方案将电力系统事件划分为故障、功率波动和电压不稳定。本文还提出了一种新的指标，即继电器排名指标，用于识别最容易因功率波动和电压不稳定而发生误动作的继电器。所提出的支持向量机分类器可以与传统的距离继电器单元协同工作。该方案已在9总线WSCC系统和39总线New England系统上进行了性能测试。
Distance relays, in the power transmission systems, are susceptible to the maloperation under certain system events, such as power swings and voltage instability, which drive the apparent impedance trajectories into the protection zones of the relay. Fast and reliable detection of the symmetrical faults, occurring during power swings, poses another challenge to operation of the distance relays. This paper introduces a new classification and protection scheme based on support vector machines (SVMs) for offering supervisory control to the operation of the conventional distance relays. The proposed scheme segregates the power system events into faults, power swings, and voltage instability. This paper also proposes a new index, called the relay ranking index, for identifying the relays most vulnerable to the maloperation due to power swings and voltage instability. The proposed SVM classifiers can work in unison with the conventional distance relay unit. The performance of the proposed scheme has been tested on a nine-bus WSCC system and 39-bus New England system.