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基于IRBFNN和PCA的电网预想故障安全运行评估方法研究
引用本文:刘尚伟,吴玲,赵友国,赵瑞锋,潘凯岩,阎同东,吴昌川.基于IRBFNN和PCA的电网预想故障安全运行评估方法研究[J].防灾减灾工程学报,2020(4):1-6.
作者姓名:刘尚伟  吴玲  赵友国  赵瑞锋  潘凯岩  阎同东  吴昌川
作者单位:东方电子股份有限公司技术中心,山东 烟台 264000;广东电网有限责任公司电力调度控制中心,广东 广州 510600
摘    要:为了更快速直观地监视、分析和评估故障后电网的安全运行状态,提出了基于径向基函数(radical basis function,RBF)神经网络和主成分分析法(principal component analysis,PCA)的评估模型。利用带衰减因子的吸引力传播(affinity propagation,AP)聚类算法选择RBF神经网络中心和隐含层节点数,同时提出了扩展的电网运行状态安全评估指标,利用越限指标权重和指数阶数避免了安全评估的遮蔽现象,利用主成分分析选取RBF神经网络的输入矢量特征,最后通过IEEE-30节点仿真算例验证了所提模型的有效性。

关 键 词:预想故障    特征选取    径向基函数神经网络    AP聚类    主成分分析

Research on security evaluation of power grid operation with contingency based on IRBFNN and PCA
LIU Shangwei,WU Ling,ZHAO Youguo,ZHAO Ruifeng,PAN Kaiyan,YAN Tongdong,WU Changchuan.Research on security evaluation of power grid operation with contingency based on IRBFNN and PCA[J].Journal of Disaster Prevent and Mitigation Eng,2020(4):1-6.
Authors:LIU Shangwei  WU Ling  ZHAO Youguo  ZHAO Ruifeng  PAN Kaiyan  YAN Tongdong  WU Changchuan
Institution:Technical Center of Dongfang Electronic Co.,Ltd.,Yantai Shandong 264000 ,China;Power Dispatch and Control Center of Guangdong Power Grid Co.,Ltd.,Guangzhou Guangdong 510600 ,China
Abstract:An evaluation model based on radial basis function neural network is proposed in order to monitor,analyze and evaluate the operation state of power grid more quickly and visually after contingency. AP clustering is used to optimize the center and the number of neurons of the hidden layer.The extended evaluation indices of power grid operation security state are established,and index weights and exponent order are used to avoid the masking effect,and PCA is used for the feature selection. The simulation on IEEE-30 bus system shows the effectiveness of the proposed model.
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