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Power System Transient Stability Assessment Method Based on Convolutional Neural Network

机译:基于卷积神经网络的电力系统暂态稳定评估方法

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A method based on convolutional neural network is proposed for power system transient stability assessment in this paper, which can overcome the shortcomings of traditional evaluation methods and satisfy the requirements with high assessment accuracy of power system transient stability assessment problems. Firstly, the structural characteristic of convolutional neural network is introduced in this paper, then the applicability in transient stability assessment problems is analyzed. Secondly, the training methods of convolutional neural network are optimized according to the characteristics of transient stability assessment problem, and the batch normalization algorithm is added to establish the transient stability assessment model. Finally, the simulation performed on the New England 10-machine 39-node system demonstrates the effectiveness of the proposed method.
机译:提出了一种基于卷积神经网络的电力系统暂态稳定评估方法,该方法克服了传统评估方法的不足,可以满足电力系统暂态稳定评估问题的高评估精度要求。首先介绍了卷积神经网络的结构特征,然后分析了其在暂态稳定性评估中的适用性。其次,根据瞬态稳定性评估问题的特点,优化了卷积神经网络的训练方法,并加入了批量归一化算法,建立了瞬态稳定性评估模型。最后,在新英格兰10机39节点系统上进行的仿真证明了该方法的有效性。

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