面向能源互联网智能感知的边缘计算技术研究

Research on Edge Computing Technology for Intelligent Sensing Layer of Energy Interconnection

随着能源互联网建设的持续推进,大量的传感器接入到系统中,获取的感知数据是海量级的,导致系统传输压力大、主站计算负荷重。传统的传感信息获取处理方式存在数据良莠不齐、数据缺失、格式不统一的问题,引入边缘计算技术定义了智能感知的系统框架,就地实现数据的处理与判决,通过云边协同机制优化系统设计。文章首先给出了多参量智能感知数据优化传输方法,其次提出了面向多参量感知的边缘计算算法的设计方法,涉及数据统一、数据辨识、分布式群智几方面,最后落地在输电线路巡检,在微风振动、舞动分析、增容设计、视频分析、云边升级等方面做了尝试。

With the continuous development of energy interconnection,a large number of sensors are installed,and the massive data lead to the system transmission pressure and heavy computing load of the master station.Some problems such as uneven data quantity,data loss and ununiform data format,occur by using the traditional way.Edge computing is introduced to redefine the system framework of intelligent perception.It can realize data processing and decision making locally,and optimize the system design through the cloud-edge collaboration mechanism.First,the optimized data transmission method is given.Second,the design method of edge calculation algorithm for multi parameter perception is proposed,which involves data modeling,data identification,distributed swarm intelligence.Finally,some attempts such as breeze vibration,galloping analysis,capacity expansion design,video analysis,cloud-edge upgrade,are explored in the aspects of transmission line monitoring.