摘要
为了能更直观地反映区域输电网发生雷击跳闸的风险,定义了以雷电定位数据为基础的输电线路雷击风险,并依据输电线路跳闸率计算模型,建立了雷击跳闸风险评估模型。模型依据雷电反击输电杆塔的规程法和雷电绕击输电线路的改进电气几何模型,以雷电参数和地形地貌参数共同作用来计算输电线路雷击跳闸风险。计算中根据雷电参数和地形地貌参数具有空间分布规律这一特征,采用网格法将目标区域划分为若干个小网格,将统计所得的网格内地闪密度参数、地面倾角和典型杆塔参数代入雷击跳闸风险评估模型中求得网格的风险值。按照自然分割法将不同网格划分为相应的风险等级,用不同颜色表示各风险等级区域,形成了区域输电网的雷击风险分布图。相关性分析表明:相比地闪密度分布图,雷击跳闸风险分布图与输电线路雷击跳闸故障点分布的相关性更强。
In order to reflect lightning trip risk of the regional transmission grid more directly,we define a transmission line lightning risk based on the lightning location data and set up a lightning trip risk assessment model according to the calculation model of transmission line trip rate.Based on the law of tower back flashover and the improved electrical geometric model of transmission line shielding,the new model calculates the risk of transmission lightning trip in accordance with the combined effects of the lightning parameters and topography parameters.In the calculation,according to the spatial distribution characteristics of lightning parameters and topography parameters,the target area is divided into several small grids with the grid method,and the lightning trip risk of each small grid is calculated using the statistics of grid flash density parameters in the mainland,surface inclinations and typical tower parameters.Moreover,by using the natural segmentation method,the grids are divided into several corresponding risk levels that are labeled by different colors,and format the lightning risk distribution map of the regional transmission grid.Correlation analysis shows that the lightning trip risk distribution map is more relevant than the ground flash density distribution map to the lightning trip failure point distribution map of transmission lines.
出处
《高电压技术》
EI
CAS
CSCD
北大核心
2012年第11期2934-2941,共8页
High Voltage Engineering
基金
国家重点基础研究发展计划(973计划)(2009CB7-24507)
广东电网公司科技项目(06HK100101)~~
关键词
输电线路
雷击跳闸
雷电定位系统
地闪密度
地面倾角
风险
风险评估模型
分布图
相关性
transmission line
lightning trip
lightning location system
ligtening density
ground inclination
risk
risk assessment model
distribution map
correlation