| 基于反向传播神经网络的发电机进相能力建模研究 |
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| 引用本文： | 王成亮,王宏华,徐钢.基于反向传播神经网络的发电机进相能力建模研究[J].电网技术,2011,35(11):136-140. |
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| 作者姓名： | 王成亮 王宏华 徐钢 |
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| 作者单位： | 1. 江苏方天电力技术有限公司,江苏省南京市,211102
2. 河海大学能源与电气学院,江苏省南京市,210098 |
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| 摘 要： | 提出一种基于反向传播神经网络（back propagation neural network，BPNN）的发电机进相能力建模新方法。该BPNN含2个隐层和1个输出层，以发电机有功和无功功率为输入，以发电机功角、电网电压为输出。以典型工况下的发电机进相运行试验结果作为训练样本和测试样本，建立了某600Mw发电机进相能力B...
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| 关 键 词： | 反向传播神经网络 发电机进相 泛化 |
Modeling of Generator Leading Phase Ability Based on Back Propagation Neural Network |
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| WANG Chengliang,WANG Honghua,XU Gang.Modeling of Generator Leading Phase Ability Based on Back Propagation Neural Network[J].Power System Technology,2011,35(11):136-140. |
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| Authors: | WANG Chengliang WANG Honghua XU Gang |
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| Affiliation: | 1(1.Frontier Electric Technology Co.,Ltd.,Nanjing 211102,Jiangsu Province,China; 2.College of Energy and Electrical Engineering,Hohai University,Nanjing 210098,Jiangsu Province,China) |
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| Abstract: | A new back propagation neural network(BPNN)-based method for the modeling of generator leading phase ability is proposed.The BPNN possesses two hidden layers and a output layer and taking the active and reactive power as inputs and the generator angle and network votlage as output.Taking the resuts of generator leading operation test under typical operation conditions as training sampling and test sampling,a BPNN model of leading phase ability of a certain 600 MW generator is built.With a view of optimal convergence accuracy,in the model design the number of hidden layers,neurons of the model as well as its transfer function are optimized.Results of both simulation and leading phase tests show that the proposed modeling method,which can effectively overcome the boundedness of traditional analysis method,possesses strong generalization ability and the model designed by the proposed method is accurate. |
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| Keywords: | back propagation neural network(BPNN) generator leading phase generalization |
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