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In the context of increasingly severe global climate problems, it is of great significance to promote low-carbon development. In order to further optimize the low-carbon behavior of residential side electricity consumption, a low-carbon collaborative method of residential flexible resources was proposed considering the characteristics of load timing. This paper analyzes the demand response characteristics of resident flexible resources and classifies various common resident flexible resources. In addition, considering the time characteristics of residential load and its correlation with external environmental factors, the probability model of residential flexible resource energy use was constructed based on Bayesian network, and the time sequence characteristics of residential electricity consumption behavior were further analyzed, so as to realize the comfort modeling of household appliances load considering the time sequence characteristics. At the same time, the real-time carbon emission factor was introduced, and the constraints such as user comfort were taken into account. A low-carbon collaborative optimization model of residential flexible resources was proposed considering load timing characteristics. The simulation results show that the proposed optimization model can not only improve the electricity economy of the user, but also effectively reduce the carbon emission of the user side, so as to realize the multi-objective optimization of economy and low carbon.