曲朝阳, 杨琴, 杨杰明, 柳伟青, 曲楠. 基于贝叶斯网络的智能变电站风险关联模型[J]. 电力系统自动化, 2016, 40(2): 95-99.
引用本文: 曲朝阳, 杨琴, 杨杰明, 柳伟青, 曲楠. 基于贝叶斯网络的智能变电站风险关联模型[J]. 电力系统自动化, 2016, 40(2): 95-99.
QU Zhaoyang, YANG Qin, YANG Jieming, LIU Weiqing, QU Nan. Risk Associated Model of Smart Substations Based on Bayesian Network[J]. Automation of Electric Power Systems, 2016, 40(2): 95-99.
Citation: QU Zhaoyang, YANG Qin, YANG Jieming, LIU Weiqing, QU Nan. Risk Associated Model of Smart Substations Based on Bayesian Network[J]. Automation of Electric Power Systems, 2016, 40(2): 95-99.

基于贝叶斯网络的智能变电站风险关联模型

Risk Associated Model of Smart Substations Based on Bayesian Network

  • 摘要: 鉴于在整体上进行智能变电站风险自动分析对日渐复杂的电力系统安全运行有着十分重要的意义,提出并设计了基于贝叶斯网络的智能变电站风险关联模型。首先,基于专家群决策方法确定智能变电站的设备风险及风险诱发因素,建立风险分析决策表,利用粗糙集求取最佳风险约简组合;然后,根据约简决策表自动建立风险关联贝叶斯网络图,提出了采用伽玛分布函数联合专家知识并融入监测数据来更新模型的条件概率分布的方法。最后,对220kV变电站进行实例分析,利用贝叶斯网络的反向推理功能实现风险诱发概率推理,实验结果证明了该模型的有效性和适用性。

     

    Abstract: In view of the great importance of automatic risk analysis in smart substations for the safety of increasingly complicated power systems,a risk associated model of smart substation based on Bayesian network(BN)is presented.Firstly,after the main risk factors and their relations are identified through experts’knowledge,a decision table of risk analysis is built and reduced through the reduction approach of the rough set theory.Then,the risk associated model is built based on BN as well as the reduced decision table,the solution of generating and updating conditional probability distribution(CPD)of model is brought forward in conjunction with experts knowledge and gamma function,while updating with monitored data considered.By taking a 220 kV substation as an example,the probabilities of risk considered with or without monitored data respectively,are predicted using reverse reasoning of BN.As the analysis results under different conditions have pre-warning function,the effectiveness and applicability of the proposed model is verified.

     

/

返回文章
返回