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On-line dynamic voltage instability prediction based on decision tree supported by a wide-area measurement system

机译:基于决策树的广域测量系统支持的在线动态电压不稳定性预测

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In this study, a new decision tree-based method is proposed to assess the small disturbance (limited to load disturbance) voltage stability of power systems by only using synchronised phasors (synchrophasors) measured by phasor measurement units in a wide-area measurement system. To properly predict the voltage instability considering various load increase directions as well as load increase step sizes, a mathematical morphology algorithm is used to extract appropriate features from synchronised measured voltage phasors during the few seconds just after the disturbance. These features along with the pre-disturbance ones are then applied to a trained decision tree to predict the voltage instability of the power system. The proposed method is applied and tested on the Nordic32 test system. To examine the efficiency and accuracy of the proposed method, the dynamic behaviours of on-load tap changing transformers as well as the stator current limiters of synchronous generators are considered. The simulation results demonstrate that this method effectively predicts the voltage instability of the power system during the first two seconds just after the disturbance, for the test system.
机译:在这项研究中,提出了一种基于决策树的新方法,通过仅在广域测量系统中使用相量测量单元测量的同步相量(synchrophasors)来评估电力系统的小扰动(限于负载扰动)电压稳定性。为了在考虑各种负载增加方向以及负载增加步长的情况下正确预测电压不稳定性,在干扰发生后的几秒钟内,使用数学形态学算法从同步测得的电压相量中提取适当的特征。然后将这些特征与预扰动一起应用于经过训练的决策树,以预测电力系统的电压不稳定性。该方法在Nordic32测试系统上得到了应用和测试。为了检验所提方法的效率和准确性,考虑了有载抽头变换变压器的动态特性以及同步发电机的定子限流器。仿真结果表明,对于测试系统,该方法可以有效地预测出刚发生扰动后的前两秒内电力系统的电压不稳定性。

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