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Transient Stability Analysis of Electrical Power Systems Using a Neural Network Based on Fuzzy ARTMAP

机译：基于模糊艺术图的神经网络电力系统瞬态稳定性分析

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摘要

This work presents a methodology to analyze transient stability for electric energy systems using artificial neural networks based on fuzzy ARTMAP architecture. This architecture seeks exploring similarity with computational concepts on fuzzy set theory and ART (Adaptive Resonance Theory) neural network. The ART architectures show plasticity and stability characteristics, which are essential qualities to provide the training and to execute the analysis. Therefore, it is used a very fast training, when compared to the conventional backpropagation algorithm formulation. Consequently, the analysis becomes more competitive, compared to the principal methods found in the specialized literature. Results considering a system composed of 45 buses, 72 transmission lines and 10 synchronous machines are presented.
机译：该工作提出了一种方法来分析基于模糊艺术架构的人工神经网络的电能系统的瞬态稳定性。该架构寻求与模糊集理论和艺术（自适应共振理论）神经网络的计算概念探索相似性。艺术架构表现出可塑性和稳定性特征，这是提供培训和执行分析的基本品质。因此，与传统的反向衰退算法配方相比，它被使用非常快的训练。因此，与专业文献中发现的主要方法相比，分析变得更具竞争力。结果表明，介绍了由45个总线组成的系统，72个传输线和10个同步机组成的系统。

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