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河南电网“污闪”故障的综合气象因素分析

发布时间:2019-06-29 17:21
【摘要】:综合考虑河南省范围内电网污闪故障的时空分布特征及地理地貌特征,利用河南省电网污闪故障数据及地面气象观测数据,研究首先确定了与该地区电网污闪故障密切相关的积污持续时间、近地层逆温、相对湿度、风速风向等环境气象特征参数,然后采用时空匹配、统计阈值分析和综合气象指标调整优化等手段,对各特征参数的综合阈值进行了初步评定,最终建立了河南省电网污闪故障的可定量化综合气象分析指标及对应气象条件:高湿、弱风、前期少雨、近地面大气层结稳定。该指标较好地拟合了气象环境条件与污闪故障之间的关系,检验结果显示指标无漏报,且空报率低于10%;基于该指标计算的多年平均条件下,河南地区污闪故障多发生在冬季,且河南东北部为电网污闪故障高发区。研究成果为河南地区的电网污闪故障防御提供了技术支持。
[Abstract]:Considering the temporal and spatial distribution characteristics and geographical and geomorphological characteristics of pollution flashover fault in Henan Province, using the pollution flashover fault data and surface meteorological observation data of Henan power grid, the environmental meteorological characteristic parameters, such as pollution duration, near formation inversion, relative humidity, wind speed and wind direction, which are closely related to pollution flashover fault in this area, are determined, and then the matching between time and space is adopted. By means of statistical threshold analysis and comprehensive meteorological index adjustment and optimization, the comprehensive threshold of each characteristic parameter is preliminarily evaluated. Finally, the quantitative comprehensive meteorological analysis index and corresponding meteorological conditions of pollution flashover fault in Henan power grid are established: high humidity, weak wind, less rain in the early stage and stable near the surface atmosphere. The index fits the relationship between meteorological environment conditions and pollution flashover fault well, and the test results show that the index has no missed report, and the empty report rate is less than 10%. Under the average conditions calculated by this index for many years, most of the pollution flashover faults in Henan area occur in winter, and the northeast of Henan Province is the area with high incidence of pollution flashover faults in power grid. The research results provide technical support for power grid pollution flashover fault prevention in Henan Province.
【作者单位】: 中国气象局公共气象服务中心;国家电网河南省电力公司电力科学研究院;
【基金】:国家电网公司重大基础前瞻科技项目(SG20141187)资助
【分类号】:TM73;P49

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