地理空间信息2025，Vol.23Issue(5)：12-17,6.DOI:10.3969/j.issn.1672-4623.2025.05.003
基于HLM和GWR技术的电网低压故障风险影响因子分析
Influence Factor Analysis of Low-voltage Fault Risk in Power Grid Based on HLM and GWR Techniques
摘要
Abstract
In order to comprehensively analyze the multi-element of power grid fault risk,based on the integration of spatio-temporal big data in the power industry,the characteristics of urban spatial dependence and spatial heterogeneity of multi-source data such as meteorological data,disaster data,urban population,POI,and the differences of multiple elements'scales,we used multi-layer linear regression(HLM)and geographically weighted regression(GWR)techniques to comprehensively model the spatio-temporal distribution characteristics of power grid fault risk.Taking the low-voltage fault risk of Guangzhou power grid in 2017 for example,HLM model revealed the multi-scale hierarchical characteristics of relevant influence factors.In addition,we constructed different GWR models according to year and month,and the results showed that the main influence factors and their correlation strengths of low-voltage fault risk of power grids varied greatly in different months and regions.Overall,HLM model focuses on the hierarchical structure analysis of influence factor relationships,while GWR model focuses on the quantitative analysis of influence factor relationships at a fine scale,providing a multi-perspective,fine-grained technical methodology to support the prevention and management of power grid fault risk.关键词
电网故障/HLM/GWR/空间统计/空间异质性Key words
power grid fault/HLM/GWR/spatial statistics/spatial heterogeneity分类
天文与地球科学引用本文复制引用
冯国平,余传坤,卢宾宾..基于HLM和GWR技术的电网低压故障风险影响因子分析[J].地理空间信息,2025,23(5):12-17,6.基金项目
国家自然科学基金面上项目(42071368). （42071368）
