Research of pattern recognition on resident power consumption behavior based on massive data plays a crucial role in power grid load prediction and demand response potential development. However

the emergence of large-scale data and multi-dimensional features of residents’electricity consumption has become a difficulty in identifying the heterogeneous pattern of residents' electricity consumption. Firstly

based on the large-scale residential electricity consumption data

the power load characteristic decomposition technology is used to construct the feature project. And then

the multi -dimensional features constructed are fused by factor analysis

and the clustering algorithm is adopted to identify the residential electricity consumption pattern. Finally

taking Jiangxi province residents’electricity consumption data as an example

an empirical analysis is made in both households and community level

and four typical residents’electricity consumption patterns have been obtained

which can provide scientific support for the grid companies to make tailored and differentiated policies and further expand the depth and breadth of services.