It has become a trend that application workflows with different computing requirements are migrated to the cloud for execution. From the perspectives of cloud data centers and users, energy consumption and satisfying users' reliability and deadline constraints have become a key problem. To solve the problem, we propose an algorithm for reliability improvement and energy-efficient of multi-workflow scheduling with deadline and reliability constraints (MRE). The MRE algorithm divides the scheduling of workflows into 2 phases: pre-scheduling and re-scheduling. In the phase of pre-scheduling, the priority of each task is calculated based on the deadline and reliability constraints. The resource that can finish the task earliest is selected and all workflows are scheduled. According to the remaining deadline constraints of workflows in the pre-scheduling, the tasks are re-scheduled using the DVFS technique in the phase of re-scheduling. Experimental results indicate that compared with other state-of-the-art algorithms, the MRE algorithm can effectively improve the number of successfully scheduled workflows and reduce energy consumption under the constraints of deadline and reliability.