Abstract:In the process of studying the near-medium-term load prediction method of the substation area, we are faced with the problem of how to use big data identification station area for industry classification. After the research, this problem is divided into the substation area industry classification method and industry load characteristics. The industry classification of the substation area determines the classification method of the second-level classification of the typical daily year (maximum) load curve in the substation area by using the k-means algorithm in data mining, and the industry load characteristic study analyzes the industry load characteristics on the basis of the industry classification of the substation area. Includes typical daily load characteristics and annual load characteristics. And this method in Shenzhen big data platform for the Shenzhen substation area industry classification and classification characteristics analysis. After the classification of the public-specific change substation area district in the industry classification, the residents'' living area is analyzed, and two categories are formed, respectively, based on the resident load and the school load. Industry load characteristics analysis to take the school substation area district as an example, to whether the students accommodation is separate, you can distinguish between out-of-school schools and residential schools. The results show that this method works well.