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In view of the large amount of calculation, high energy consumption, low efficiency, and poor deployment accuracy of traditional cloud computing task scheduling models, a new cloud computing task scheduling model is designed based on dynamic energy perception. Based on dynamic energy perception, three parameters such as the utilization rate of the central processing unit of the resource allocation server, the occupancy rate of the memory, and the load rate of the controller are selected to construct a three-dimensional cloud computing task node projection space, and the above parameter vectors are projected into the space middle. Introduce dynamic energy perception to establish a cloud computing task scheduling model, use virtual technology to merge multiple servers into one server, analyze and classify scheduling tasks, and use energy perception algorithms to assign tasks to be scheduled to virtual resources that meet scheduling requirements. Tasks are scheduled to server resources to achieve task scheduling. The experimental results show that the cloud computing task scheduling model based on dynamic energy perception can effectively shorten the scheduling time and reduce the scheduling energy consumption from both the small task set and the large task set.