数字孪生技术下输变电设备运行状态智能感知

Intelligent Perception of Operation State of Power Transmission and Transformation Equipment Based on Digital Twin Technology

随着用电需求的不断提高,输变电设备技术飞速发展、数量逐年递增,针对传统输变电设备信息难以实时更新、运检工作耗时费力、人力财力消耗大的问题,提出了基于数字孪生技术的运行状态智能感知方法,建立了输变电设备数字孪生模型。其中感知层用来读取全局信息,网络层用来整合多源异构数据并归类,平台层基于深度神经网络算法对数据进行处理并存储,应用层针对用户需求实现实时智能感知的功能。上述模型在虚拟数字空间基于多方法混合建模的策略对设备进行三维数字建模,通过虚实映射方法达到实时可视化功能,实现输变电设备智能感知和在线诊断。实验结果证明,相比传统传感器方法,新方法在温度感知方面准确度提升约3%,电流测量方面准确度提升4%,更能反映设备运行状态,促进了输变电设备状态感知领域的数字孪生技术的发展和应用。

With the continuous improvement of power demand,the technology of power transmission and transfor⁃mation equipment is developing rapidly and the number is increasing year by year.In order to solve the problems of traditional power transmission and transformation equipment,such as difficult to update information in real time,time-consuming and laborious operation inspection,and large consumption of human and financial resources,this paper proposes an intelligent perception method of operation state based on digital twin technology,and establishes a digital twin model of power transmission and transformation equipment.Among them,the perception layer is used to read global information,the network layer is used to integrate and classify multi-source heterogeneous data,the platform layer processes and stores data based on deep neural network algorithm,and the application layer realizes real-time intelligent perception function according to user needs.The model conducts 3D digital modeling of equipment based on the strategy of multi method hybrid modeling in virtual digital space,achieves real-time visualization function through virtual reality mapping method,and realizes intelligent perception and online diagnosis of power transmission and transformation equipment.The experimental results show that compared with the traditional sensor method,the accuracy of this method in temperature sensing is improved by 3%at least,and the accuracy of current measurement is improved by 4%,which can better reflect the operating state of equipment,and promote the development and application of digital twin technology in the field of state sensing of power transmission and transformation equipment.