中国电机工程学报2026，Vol.46Issue(10)：3953-3966,中插3,15.DOI:10.13334/j.0258-8013.pcsee.241972
基于条件信息熵的电力系统行业用电数据因果性定量分析方法
Quantitative Causality Analysis of Industrial Electricity Consumption Data Based on Conditional Information Entropy
摘要
Abstract
Electricity consumption data not only represents the load demand for power users,but also shows a close connection between the production and residence in modern society.The macro and micro consumption data contain information about regional electricity demand and individual consumption behavior,which hold practical value in applications such as load forecast,power-economic analysis and system operation.However,information like dominant industry or industrial chain structure contained in sectoral electricity consumption data in intermediate perspective has not been fully revealed.To this end,a quantitative analysis method based on conditional information entropy for multi-time series data in power system is proposed and applied to analyze the causal relationship between industrial electricity consumption data.Case studies based on real data from Jan.2017 to Jul.2023 are conducted both qualitatively and quantitatively to validate the effectiveness of the proposed method.关键词
信息熵/因果分析/行业用电量/工业用电量Key words
information entropy/causal analysis/sectoral electricity consumption/industrial power consumption分类
信息技术与安全科学引用本文复制引用
张广伦,钟海旺..基于条件信息熵的电力系统行业用电数据因果性定量分析方法[J].中国电机工程学报,2026,46(10):3953-3966,中插3,15.基金项目
国家自然科学基金联合基金项目(U24B2077).Project Supported by the Joint Fund of National Natural Science Foundation of China(U24B2077). （U24B2077）
