一种基于气象大数据的电网气象类故障快速研判方法研究

Research on a Rapid Detection Method for Power Grid Faults Based on Meteorological Big Data

电网大部分故障跳闸都与气象条件有关,掌握电网实时气象情况,对于指导电网快速故障研判、提升故障处置效率具有重要意义。本文阐述了影响电网安全运行的主要气象类型、对电网故障跳闸的诱发机制以及相应的故障研判依据,通过集成多源气象数据,基于三维电网GIS,建立了电网气象故障的大数据分析模型,实现对气象类电网故障的快速研判。本文提出的气象诊断分类方法和基于气象样本均值的相似性分析模型,充分、合理利用了现有的电网气象资源,优化、简化了同类概率研判模型,为电网气象类故障的快速研判提供了新的见解和方法。

Most of fault trips in power grid are related to weather conditions.It is of great significance to apply the real-time weather conditions to guide the fast fault determination and to improve the efficiency of the fault disposal.In this paper,the main meteorological types which affect the safety of power grid are summarized.The weather-inducing mechanism to the grid trip is explained and the basis for the fault determination is proposed.By integrating multi-source meteorological data,a big data analysis model for the quick determination of meteorological faults in power grid is established based on the 3D GIS.The meteorological classification method and the comprehensive evaluation algorithm based on the mean of meteorological parameters proposed in this paper make full and rational use of the existing meteorological resources in power grid,optimize and simplify the traditional model,and provide new insights and methods for the meteorological faults determination in power grid.