摘要
根据配电网系统结构、设备分布特点,针对电力工业配电网数据通信规范对WSN的要求,研究了一种基于模糊认知图理论和马尔科夫链建立智能配电网WSN数据传输模型。定性分析了影响网络数据传输性能指标的主要因素,构造了模糊认知图模型所包含的五类概念顶点集合。利用马尔科夫链建立了配电网节点数据缓冲队列模型,给出了节点竞争信道状态概率的计算分析方法。在不同的配电网数据产生率下对模型进行仿真实验研究,结果表明,高优先级的通信数据有较低的传输延迟和较高的有效吞吐率、可靠性,所提出的方法可为配电网WSN数据通信提供Qo S保障。
According to the characteristics of system structure and equipment distribution of distribution network, an intelligent distribution network WSN data transmission model based on fuzzy cognitive map theory and Markov chain was built for the WSN requirements from the data communication specification of electric power industry distribution network. The main factors influenced the network transmission performance were analyzed qualitatively, and the five types of concept vertex contained in fuzzy cognitive map models were constructed. Moreover, the data buffer queue model of distribution network node was established through the Markov chain, and a computational analysis method was given to calculate the state probability of competition channel. The simulation experiments for model in different data generation rate were carried out. The result shows that high priority communication data has lower transmission delay and higher effective throughput, reliability, and the method proposed in this paper can provide QoS guarantee for WSN in distribution network communication.
出处
《电子测量与仪器学报》
CSCD
北大核心
2016年第1期66-74,共9页
Journal of Electronic Measurement and Instrumentation
基金
2015年度安徽省电气传动控制重点实验室开放基金(201503)课题
