用低速率同步相量数据评估电力系统稳定性

Sharda Tripathi, S. De
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引用次数: 6

摘要

本文研究了一种基于o-支持向量回归(o-SVR)的数据驱动方法来识别当前电力线频率样本对过去几个样本的依赖关系。在标准实践中,相量测量单元(pmu)连续测量来自电网中不同总线位置的频率样本,并以固定速率(通常为25个样本/秒)将其传输到相量数据集中器(PDC)。该策略的目标是降低PMU的采样率或固定速率采样从PMU到配电柜的传输速率,以便在不影响电力系统稳定性的情况下早期检测到电力系统中任何即将发生的干扰。我们通过量化样本数据率降低,并获得电网稳态和扰动状态下的平均预测误差来评估所提出模型的性能。
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Assessment of power system stability using reduced-rate synchrophasor data
In this paper, we investigate a data driven approach based on o-Support Vector Regression (o-SVR) to identify the dependence of present sample of power-line frequency on past few samples. In standard practice, the Phasor Measurement Units (PMUs) measure the frequency samples continuously from various bus locations in the power grid and transmit them at a fixed rate, typically at 25 samples/sec, to the Phasor Data Concentrator (PDC). Objective of the proposed strategy is to reduce the sampling rate at a PMU or transmission rate of the fixed-rate samples from a PMU to the PDC such that any impending disturbance in the power system can be detected early without compromising stability of the power system. We evaluate the performance of our proposed model by quantifying the sample data rate reduction and obtaining the average prediction error during the steady state as well as disturbed state conditions in the power gird.
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