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New method for generators' angles and angular velocities prediction for transient stability assessment of multi-machine power systems using recurrent artificial neural network

机译:递归人工神经网络的多机电力系统暂态稳定评估中发电机角和角速度预测的新方法

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Summary form only given. Recurrent radial basis function (RBF), and multi-layer perceptron (MLP) artificial neural network (ANN) schemes are proposed for dynamic system modeling, and generators' angles and angular velocities prediction for transient stability assessment. The method is presented for multi-machine power systems. In this scheme, transient stability is assessed based on monitoring generators' angles and angular velocities with time, and checking whether they exceed the specified limits for system stability or not. Data generation schemes have been proposed. The proposed recurrent ANN scheme is not sensitive to fault locations. It is only dependent on the post-fault system configuration.
机译:仅提供摘要表格。针对动态系统建模,提出了递归径向基函数(RBF)和多层感知器(MLP)人工神经网络(ANN)方案,并针对瞬态稳定性评估,对发电机的角度和角速度进行了预测。提出了用于多机动力系统的方法。在此方案中,基于随时间监视发电机的角度和角速度,并检查它们是否超过系统稳定性的指定限制,来评估瞬态稳定性。已经提出了数据生成方案。所提出的递归ANN方案对故障位置不敏感。它仅取决于故障后系统配置。

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