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SECURITY ANALYSIS OF DISTRIBUTION NETWORK USING NONLINEAR LOAD FLOW AND ARTIFICIAL INTELLIGENCE

机译:基于非线性负荷流和人工智能的配电网安全性分析

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Power system security assessment by static approach is considered in the paper. The objective of the presented work is to investigate post-contingency load flows implementing back-propagation neural network. The chosen neural network is to perform the post-contingency classification, and to indicate the operating limit violation. Presented solution deals with overload and low voltage coefficients, which are calculated for important lines and nodes using nonlinear post-contingency load flow. A 600 node power system has been used to investigate the performance of neural network for security analysis of the meshed distribution network, being a part of that analyzed network.
机译:本文考虑采用静态方法进行电力系统安全评估。提出的工作的目的是研究实施反向传播神经网络的意外事故后的潮流。所选择的神经网络将执行意外事件后的分类,并指示违反操作极限的情况。提出的解决方案涉及过载和低电压系数,这些系数是使用非线性事后应变潮流为重要线路和节点计算的。一个600节点的电力系统已被用于调查神经网络的性能,以进行网状配电网络的安全性分析,这是该分析网络的一部分。

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