Blackouts in our daily life can be disastrous with enormous economic loss. Blackouts usually occur when appropriate corrective actions are not effectively taken for an initial contingency. Therefore, it is critical to complete those tasks that are running power grid computing algorithms in the Energy Management System (EMS) in a timely manner to avoid blackouts. This problem can be formulated as guaranteeing end-to-end deadlines in a Distributed Real-time Embedded (DRE) system. However, existing feedback scheduling algorithms in DRE systems cannot be directly adopted to handle with significantly different timescales of power grid computing tasks. In this paper, we propose a hierarchical control solution to guarantee the deadlines of those tasks in EMS by grouping them based on their characteristics. Furthermore, we present an adaptive control scheme to achieve analytical assurance of control accuracy and system stability, in spite of significant system variation. Our solution is based on well-established control theory for guaranteed control accuracy and system stability and can adapt to changes in the system model without manual reconfiguration and profiling. Simulation results based on a realistic workload configuration demonstrate that our solution can guarantee timeliness for power grid computing and hence help to avoid blackouts.
['Ming Chen', 'Xiaorui Wang', 'Clinton Nolan']
Hierarchical CPU utilization control for real-time guarantees in power grid computing