To address power supply pressure and safety hazards in high-density residential communities caused by dense population and surging electricity demand

this paper proposes an early warning method for electricity safety hazards based on electric power big data. It integrates multidimensional indicators

including average monthly electricity consumption per household

average capacity per household

and the ratio of electricity consumption to capacity

and applies the K-means clustering algorithm to analyze electricity consumption data of communities within the service area. The communities are divided into five categories

including high-density residential community

potential risk

high-load risk

high household count risk

and low risk. Differentiated risk early warning rules are established

and targeted governance measures are proposed.