For large -scale High Performance Computing centers with a wide range of different projects and heterogeneous infrastructures, efficiency is an important consideration. Understanding how compute jobs are scheduled is necessary for improving the job scheduli ng strategies in order to optimize cluster utilization and job wait times. This increases the importance of a reliable simulation capability, which in turn requires accuracy and comparability with historic workloads from the cluster. Not all job schedulers have a simulation capability, including the Portable Batch System (PBS) resource manager. Hence, PBS based centers have no direct way to simulate changes and optimizations before they are applied to the production system. We propose and discuss how to run job simulations for large-scale PBS based clusters with the Maui Scheduler. This also includes awareness of node downtimes, scheduled and unexpected. For validation purposes, we use historic workloads collected at the IT4In novations supercomputing center. The viability of our approach is demonstrated by measuring the accuracy of the simulation results compared to the real workloads. In addition, we discuss how the change of the simulator’s time step resolution affects the accuracy as well as simulation tim es. We are confident that our approach is also transferable to enable job simulations for other computing centers using PBS.