基于特征匹配的配电通信流量模型  

A Feature Matching Based Traffic Model of Power Distribution Communication Network

作　　者：唐良瑞[1] 杜施默 季石宇 

机构地区：[1]华北电力大学电气与电子工程学院,北京市102206

出　　处：《电力系统自动化》2016年第7期107-112,127,共7页Automation of Electric Power Systems

基　　金：国家高技术研究发展计划(863计划)资助项目(2014AA01A701);北京市自然科学基金资助项目(4142049);国家自然科学基金资助项目(51507063);中央高校基本科研业务费专项资金资助项目(2015XS07)~~

摘　　要：在流量建模领域自相似性和多重分形性已引起了广泛的关注,然而配电通信流量在具有上述特征的同时还表现出明显的确定性行为。鉴于一个有效的流量模型应能够捕获流量中的重要特点,文中在配电通信流量分析的基础上提出特征匹配模型。该模型利用最大熵谱分析方法将确定性流量与混沌性流量分离,同时根据混沌性流量的尺度行为特性将小时间尺度L-系统模型嵌入到大时间尺度分形高斯噪声(FGN)过程中对流量进行建模。仿真结果表明该模型不仅可以如实捕捉流量的分布概率,还具有刻画自相似性与多重分形特征的能力。Self-similarity and multi-fractal have attracted much attention in the network traffic modeling field.And besides these two characteristics,traffic in the power distribution communication network also shows a kind of significant deterministic behavior.An efficient traffic model should be able to capture the most important features of network traffic flows.And for this reason,an analytical study of the traffic in power distribution communication network is presented and a new feature matching model proposed.This model divides the traffic into deterministic and chaotic flows based on a maximum entropy spectrum analysis.And for chaotic flow,according to its time scale behaviors,the L-system model of small time scale is applied in the fractal Gaussian noise（FGN）model of large time scale.It is shown by simulation results that the proposed model can not only capture the distribution probability faithfully but also depict the self-similarity and multi-fractal characteristics of the traffic.

关 键 词：配电通信 特征匹配 确定性 自相似 多重分形 

分 类 号：TM73[电气工程—电力系统及自动化]