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.