This paper presents a new approach to wide-area out-of-step (OOS) protection through predicting the power and rotor angle curves by the autoregressive moving-average (ARMA) method. To reduce the computation burden of ARMA, its parameters are estimated using an extended Kalman filter. The predictive feature of the proposed approach results in saving hundreds of milliseconds before the actual instability occurs, which can be served to activate appropriate countermeasures against wide-spread system instability. The OOS condition is detected using the extended equal area criterion developed for multimachine power systems, in which the single-machine infinite-bus model of the system is built using wide-area measurements. The proposed approach is adapted with the communication requirements of IEEE Std. C37.118, and thus, it can be used as a practical wide-area OOS protection scheme. The IEEE 39- and 118-bus systems are used to evaluate the efficiency of the proposed approach. The obtained results demonstrate the effectiveness of the proposed scheme in predicting OOS phenomena.

中文翻译：

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一种新的广域失步保护预测方法


本文提出了一种通过自回归移动平均（ARMA）方法预测功率和转子角度曲线来实现广域失步（OOS）保护的新方法。为了减少 ARMA 的计算负担，使用扩展卡尔曼滤波器来估计其参数。该方法的预测功能可以在实际不稳定发生之前节省数百毫秒，这可以用于针对广泛的系统不稳定启动适当的对策。 OOS 状况是使用为多机电力系统开发的扩展等面积准则来检测的，其中系统的单机无限总线模型是使用广域测量建立的。所提出的方法适应 IEEE 标准的通信要求。 C37.118，因此可以作为实用的广域OOS保护方案。 IEEE 39 和 118 总线系统用于评估所提出方法的效率。获得的结果证明了所提出的方案在预测 OOS 现象方面的有效性。