面向智能电网的网络态势评估模型及感知预测  

Evaluation model of network situation and its awareness prediction oriented to intelligent power grid

作　　者：杨鹏[1] 马志程[1] 靳丹[1] 蒙波宇 姜万菲 

机构地区：[1]国网甘肃省电力公司信息通信公司,甘肃兰州730050 [2]兰州理工大学计算机与通信学院,甘肃兰州730050

出　　处：《兰州理工大学学报》2015年第4期99-103,共5页Journal of Lanzhou University of Technology

摘　　要：将态势感知技术应用于智能电网中,提出一种针对智能电网的态势评估模型,结合自回归(AR)预测模型、最小二乘支持向量机(LSSVM)预测模型、RBF神经网络预测模型等预测方法,实现基于信息融合的组合预测方法.经实测数据验证分析,该方法可以有效地描述电网网络安全的态势发展情况,且预测精度高于单一的预测模型.Information security intelligent power grid is important issue concerned in national energy source security and economic lifelines. In this paper, the situation awareness technique is used in the intelligent power grid and a situation assessment model was proposed for this power grid. The autoregressive （AR） prediction model, least squares support vector machine （LSSVM） prediction model, and RBF neural network prediction model were integrated with this method to form an information fusion-based integral prediction model. It was known after analysis and validation of actually tested data, that this method could be used to effectively describe the situation development of network security of power grid, and the prediction precision would be higher than that of single prediction model.

关 键 词：智能电网 信息安全 态势感知 组合预测 

分 类 号：TM73[电气工程—电力系统及自动化]