数字孪生变电站框架设计与关键技术研究

随着智能电网快速推进与新技术领域的出现,以变电站为代表的能源互联网系统拓扑结构趋于复杂,传统运维管理模式已经难以满足变电站规划设计、监测分析和运行优化的要求。数字孪生（Digital Twin,DT）技术的发展给电力系统的智能化管理带来诸多便利。然而作为推动能源电力行业数字化、智能化的关键技术,相关研究与应用处于初期起步阶段,将数字孪生技术工程应用于能源电力各业务环节依然存在诸多挑战,亟需开展系统性研究,以突破适应能源电力行业特殊性的数字孪生关键技术。为此,本文以变电站作为应用场景,首先对变电站运维管理现状进行了分析,指出现阶段变电站巡检模式缺陷、模型精度不够、感知参量单一、缺乏对数据的深度挖掘等问题。以此设计了一套涵盖空间信息与设备建模、变电主设备机理建模、智能反馈控制、设备感知网络、基于数据驱动的数字孪生体模型的仿真,以及三维可视化渲染与应用的数字孪生变电站模型框架。然后讨论了变电站数字孪生技术面临的问题与挑战,包括：高性能、低成本、高精度、低功耗、高集成度与智能化的变电站专用传感器研制;海量多源异构数据存储管理与计算资源优化分配;孪生模型精度亟待提升与可解释性缺乏论证;“数据安全”与“数据孤岛”给数据驱动的模型训练带来挑战;高精度实景三维重建与虚拟实体动态更新算法的研究。针对提出的问题与挑战,进而探讨了解决问题的关键技术研究,包括基于压缩感知理论的新工艺、新材料的智能传感器技术;海量多源异构数据分布式云存储技术与以安全私有云为核心的数据管理体系;云边协同计算技术;数据驱动与机理知识融合建模技术;满足隐私保护和数据安全前提下的模型训练技术——可信联邦学习;实景三维重建、点云语义分割、点云动态可视化、虚拟现实等计算机视觉相关技术。结合数字孪生模型设计与关键技术问题的探讨,给出了一套面向工程应用的数字孪生变电站系统设计方案,重点阐述了包括变电站设备实时监测、设备故障诊断与故障预测、运维决策优化与智能反馈控制等典型的应用场景。数字孪生技术与变电业务各环节的深度结合,有助于智慧变电站运维管理发展与效能提升、开辟数字化智能变电站运维管理新模式。进一步,数字孪生技术的发展成熟必将推动整个能源电力行业打破数据、技术壁垒,实现电力全产业链上下游企业的价值、技术协同,构建更大范围的数字孪生系统,具有显著社会效益和战略意义。

Digital Twin Substation Framework Design And Key Technology Research

With the rapid advancement of smart grid and the emergence of new technologies, the topology of the energy Internet system represented by substations tends to be complex, and the traditional operation and maintenance management mode has been difficult to meet the requirements of substation planning and design,monitoring analysis and operation optimization. The development of digital twin (DT) technology brings many conveniences to the intelligent management of power systems.However, as a key technology to promote the digitalization and intelligence of the energy and power industry, related research and applications are still in the initial stage. There are still many challenges in applying digital twin technology engineering to various business links of energy power. Systematic research is urgently needed to break through the adaptation Key technologies of digital twin engineering application for the particularity of the energy and power industry. For this reason, this paper takes the substation as the application scenario, firstly analyzes the current situation of the operation and maintenance management of the substation, and points out the defects of the substation inspection mode, the insufficient model accuracy, the single perception parameter, and the lack of in-depth data mining. A digital twin substation model framework is designed, which includes spatial information and equipment modeling, main equipment mechanism modeling, intelligent feedback control, equipment sensing network, model simulation and 3D visualization rendering and application.Then, the problems and challenges faced by the digital twin technology of substations are discussed, including: development of dedicated sensors with high performance, low cost, high precision, low power consumption, high integration and intelligence; massive multi-source heterogeneous data storage management and computing resources Optimization allocation; twin model accuracy needs to be improved urgently and interpretability is lacking; "data security" and "data island" bring challenges to data-driven model training; research on high-precision 3D reconstruction of real scenes and dynamic update algorithms for virtual entities. In view of the problems and challenges raised, the research on key technologies to solve the problems is discussed, including new technology based on compressed sensing theory, smart sensor technology based on new materials; distributed cloud storage technology for massive multi-source heterogeneous data and secure private cloud The core data management system; cloud-edge collaborative computing technology; data-driven and mechanism knowledge fusion modeling technology; model training technology that meets the premise of privacy protection and data security - trusted federated learning; 3D reconstruction of real scenes, point cloud semantic segmentation, Computer vision related technologies such as point cloud dynamic visualization and virtual reality. Combined with the design of digital twin model and the discussion of key technical issues, a set of application-oriented digital twin substation system design scheme is given, focusing on the real-time monitoring of equipment in the station, equipment fault diagnosis and fault prediction, operation and maintenance decision optimization and intelligent feedback Typical application scenarios including control. The deep integration of digital twin technology and all aspects of the substation business will help the development and efficiency improvement of smart substation operation and maintenance management, and open up a new model of digital smart substation operation and maintenance management. Further, the mature development of digital twin technology will surely promote the entire energy and power industry to break down data and technical barriers, realize the value and technical synergy of upstream and downstream enterprises in the entire power industry chain, and build a larger-scale digital twin system, with significant social benefits and strategies.