摘要
通过梳理配网网格的网架特性和网格化规划的优势,寻找网格层面上与可靠性水平相关且便于统计的因素,并量化形成配网特征指标。将不同供电网格的特征指标与可靠性指标进行灰色关联分析,求取特征指标对可靠性水平的权重贡献度。针对传统灰色关联分析存在的问题,引入分段动态分辨系数、对关联系数模糊时间加权和计算综合灰色关联度的方法进行改进。随后根据特征指标的权重大小进行排序,筛选出权重较大即对可靠性水平影响较大的特征指标,形成可靠性综合指标体系。可靠性综合指标体系的建立,为配电系统提高供电可靠性水平提供依据。通过对某地的实例分析,证明了理论分析方法的合理性和有效性。
By combing the grid structure characteristics of distribution network and the advantages of grid planning,factors related to reliability level and easy to be counted on the grid level are found,and the characteristic indexes of distribution network are quantified.Gray correlation analysis between the characteristic indexes and the reliability index of different power supply grids is carried out to obtain the weight contribution degree of the characteristic indexes to the reliability level.In view of the problems existing in the traditional gray relational analysis,the method of segmentation dynamic resolving factors is introduced to improve the fuzzy time weighting of correlation coefficient and calculation of comprehensive gray relational degree.Then,the indexes are sorted according to the weight of the characteristic indexes,and the characteristic index with a larger weight,that is,it has a greater influence on the reliability level,is selected to form the comprehensive reliability index system.The establishment of reliability comprehensive index system provides the basis for the distribution system to improve the reliability level of power supply.The rationality and effectiveness of the theoretical analysis method are proved by an example of a certain area.
作者
安佳坤
贺春光
韩璟琳
康伟
邵华
金烨璇
An Jiakun;He Chunguang;Han Jinglin;Kang Wei;Shao Hua;Jin Yexuan(Economic Research Institute of State Grid Hebei Electric Power Company,Shijiazhuang 050021,China;School of Electronic Information and Electrical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China)
出处
《电测与仪表》
北大核心
2019年第20期1-8,共8页
Electrical Measurement & Instrumentation
关键词
供电可靠性
网格
灰色关联度
动态分辨系数
模糊加权
power supply reliability
grid
gray relational degree
dynamic resolution coefficient
fuzzy weighting
