Grid-Interactive Hyperscale Data Centers: Deep Reinforcement Learning for Joint Workload-Cooling Scheduling to Enable Demand Response and Renewable Integration
A deep reinforcement learning (DRL) framework that jointly co-schedules computing and thermal resources so that a hyperscale data center can operate as a grid-interactive flexible load and supports the evolution of hyperscale data centers from passive electricity consumers toward active, grid-interactive participants in renewable-penetrated power systems.