摘要
作为智能变电站"神经系统"的通信系统可靠性直接影响着整个变电站自动化系统的稳定和安全运行.针对智能变电站通信系统的复杂性以及各评价指标间的模糊关联性,本文提出了基于树增强型朴素可能性网络分类器的智能变电站通信网络运行状态评估方法,将通信系统的4种运行状态作为类型集,选取"可用性"、"响应时间"、"丢包率"等9个指标构成运行状态的属性集,并结合指标权重和岭形函数刻画单一实例与类型集的模糊隶属度.实验表明该方法有较好的分类精度,不仅能很好地刻画各影响因素间的相互作用,还能有效的解决智能变电站通信网络状态评估中的不确定问题.
Reliability of the communication, which is the nervous system of smart substation, has serious impact on the stability and security of the whole substation automation system. To resolve the complicity and fuzzy correlation between the evaluation indexes of the communication system in smart substation, this paper proposes a new comprehensive evaluation method of running condition for communication network in smart substation based on tree augmented nai ve possibilistic network classifier, which uses the four running states of communication network as classes set, selects nine indexes including usability, response time, packets loss rate and et.al as attributes set, describes the fuzzy membership degree of the single instance to the classes set by using the index weight and ridge function. Experiments have shown that the method has better classification accuracy. It can not only describe the interaction between the affecting factors, but also effectively resolve the uncertainty of running state evaluation of the communication network in smart substation.
出处
《河北工业大学学报》
CAS
北大核心
2014年第2期21-27,共7页
Journal of Hebei University of Technology
基金
河北省自然科学基金(E2012208006)
河北省教育厅高等学校科学研究计划自然科学重点项目(ZH2011243)
关键词
智能变电站
通信网络
可能性网络分类器
状态评估
smart substation: communicationnetwork
naive possibilistic network classifier
running condition evalu-ation