智能电网脆弱性综合评价模型的构建方法研究  

Research on the construction method of vulnerability comprehensive evaluation model of smart grid

作　　者：刘自南 Liu Zinan(Chongqing Airport Group Co.,Ltd.,Chongqing,401120,China)

机构地区：[1]重庆机场集团有限公司,重庆401120

出　　处：《机械设计与制造工程》2023年第8期107-111,共5页Machine Design and Manufacturing Engineering

基　　金：民航科技创新引导资金(MHRD20140302)。

摘　　要：通过研究智能电网脆弱性评价方案,发现评价过程中不需要任何人工介入和干预。同时,利用模糊神经网络算法,分析4个不同数据来源,编制对应的数据模糊方案,主要包括采用10个神经网络模块和7个相同算法,最终得到7个[0,1]区间上的解模糊输出值。其中,ERP和OA系统的输入数据采用模糊方案流程运行统计结果,设备节点的录波图数据以及电网拓扑量化数据采用基于TOPSIS的归一化模糊方案,输出解模糊方案采用去量纲线性投影方案将数据高保真地投影到[0,1]区间。相较以往涉及到诸多主观评价的评价方案,该方法的客观性和实时性更强,与其他大数据挖掘系统的数据整合效果更好。An objective and real-time vulnerability assessment result of smart grid is studied.There is no artificial intervention and no artificial intervention in the assessment process.Through the fuzzy neural network algorithm,different data fuzzy schemes are adopted for four data sources,10 neural network modules and 7 defuzzification schemes of the same algorithm are adopted,and finally the output values of defuzzification on seven[0,1]intervals are obtained.Among them,the input data fuzzy scheme of ERP and OA system is the process operation result statistics,the oscillogram data of equipment nodes and the topological quantitative data of power grid adopt the normalized fuzzy scheme based on TOPSIS,and the output defuzzification scheme adopts the dimensionless linear projection scheme to project the data to the[0,1]interval with high fidelity.Compared with previous evaluation schemes involving many subjective evaluations,this scheme is more objective,more real-time and better integrated with other big data mining systems.

关 键 词：智能电网 电网脆弱性 评价模型 TOPSIS 模糊神经元网络 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]