阐述了上海500kV变电站三维仿真培训系统的软硬件结构及网络部署方案,重点介绍了该系统采用的分布式仿真通信中间件(adaptive communication environment,ACE)技术。ACE是该仿真培训系统实现分布式应用的基础,为仿真应用软件提供了透明...阐述了上海500kV变电站三维仿真培训系统的软硬件结构及网络部署方案,重点介绍了该系统采用的分布式仿真通信中间件(adaptive communication environment,ACE)技术。ACE是该仿真培训系统实现分布式应用的基础,为仿真应用软件提供了透明、高效的运行管理通信环境。该系统全面仿真了上海500kV电网输变电运行的主要环节,实现了500kV变电站三维仿真培训,可以正确反映变电站、综合自动化系统和电网的相互作用、相互影响,在二次设备仿真技术、通信方式实现、培训效果等方面有较大改进。现场运行表明该系统在远程网络通信中采用的ACE技术可以减少网络通信流量,可用于电力企业网远程培训。展开更多
In wireless sensor networks,node localization is a fundamental middleware service.In this paper,a robust and accurate localization algorithm is proposed,which uses a novel iterative clustering model to obtain the most...In wireless sensor networks,node localization is a fundamental middleware service.In this paper,a robust and accurate localization algorithm is proposed,which uses a novel iterative clustering model to obtain the most representative intersection points between every two circles and use them to estimate the position of unknown nodes.Simulation results demonstrate that the proposed algorithm outperforms other localization schemes (such as Min-Max,etc.) in accuracy,scalability and gross error tolerance.展开更多
文摘阐述了上海500kV变电站三维仿真培训系统的软硬件结构及网络部署方案,重点介绍了该系统采用的分布式仿真通信中间件(adaptive communication environment,ACE)技术。ACE是该仿真培训系统实现分布式应用的基础,为仿真应用软件提供了透明、高效的运行管理通信环境。该系统全面仿真了上海500kV电网输变电运行的主要环节,实现了500kV变电站三维仿真培训,可以正确反映变电站、综合自动化系统和电网的相互作用、相互影响,在二次设备仿真技术、通信方式实现、培训效果等方面有较大改进。现场运行表明该系统在远程网络通信中采用的ACE技术可以减少网络通信流量,可用于电力企业网远程培训。
基金supported in part by the Key Program of National Natural Science Foundation of China(Grant No.60873244,60973110,61003307)the Beijing Municipal Natural Science Foundation(Grant No.4102059)
文摘In wireless sensor networks,node localization is a fundamental middleware service.In this paper,a robust and accurate localization algorithm is proposed,which uses a novel iterative clustering model to obtain the most representative intersection points between every two circles and use them to estimate the position of unknown nodes.Simulation results demonstrate that the proposed algorithm outperforms other localization schemes (such as Min-Max,etc.) in accuracy,scalability and gross error tolerance.