Aiming at the practical problems of low self -sufficient renewable energy utilization, high power purchase cost and in-adequate source -storage -charge coordination in the current energy management of active integrated energy systems, a data-driven real-time dispatching decision model is proposed. The hybrid model is firstly based on a large amount of energy consumption data for its characteristic indicators and time series characteristics, and the K -means algorithm is used for cluster analysis to obtain a representative typical energy consumption pattern. Then the parametric fuzzy inference system combined with the heuristic optimization algorithm is introduced, and the fuzzy logic inference rules are self-optimized based on the representative samples to obtain a real-time control model for the economical scheduling of energy - using systems.In the simulation calculation through the actual data set, the validity and feasibility of the model are verified.