Job Scheduler-Driven Power Gateway for High Performance Computing

Power gateways in the form of a microgrid can incorporate multiple distributed energy resources (DER) in either grid forming or grid following mode and support high performance computing (HPC) power profiles including the large load-follow requirements observed in multi-user HPC systems. The microgrid's flexibility to operate in either grid forming or grid following mode and to actively switch between these modes enables baseline power from multiple non-baseline DER while maintaining high power quality metrics for the HPC system. But this enormous flexibility in demand response and time of use shifting is generally programmed independently of any integration with an HPC job scheduler, which can better inform the load shaping by the microgrid. While there are many existing approaches where the HPC job scheduler takes in information from the grid to make queue scheduling decisions, this work takes the opposite view and explores three strategies where the forecast of jobs in the queue can change the settings of the grid. Three strategies are tested where the forecast of jobs in the queue adjusts the settings of a microgrid designed for a datacenter, in this case with three classes of HPC architectures. The strategies are demonstrated using a microgrid with 64 kW of solar capacity and 320 kWh of battery over a period of 21 days operating with significant load-follow swings, a throttled grid, cloudy conditions, switching between grid following and grid forming modes, and a wide range of battery states-of-charge, all while maintaining high quality power metrics. The strategies presented provide a mechanism for the forecast of jobs in the queue to influence and adjust the settings of a microgrid and to improve HPC power outcomes such as maximizing renewable energy usage.