Green Scheduling: Scheduling of Control Systems for Peak Power Reduction

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Real-Time and Embedded Systems Lab (mLAB)
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Scheduling; Energy Systems; Peak Power Reduction; Load Balancing;
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Heating, cooling and air quality control systems within buildings and datacenters operate independently of each other and frequently result in temporally correlated energy demand surges. As peak power prices are 200-400 times that of the nominal rate, this uncoordinated activity is both expensive and operationally inefficient. While several approaches for load shifting and model predictive control have been proposed, we present an alternative approach to fine-grained coordination of energy demand by scheduling energy consuming control systems within a constrained peak power while ensuring custom climate environments are facilitated. Unlike traditional real-time scheduling theory, where the execution time and hence the schedule are a function of the system variables only, control system execution (i.e. when energy is supplied to the system) are a function of the environmental variables and the plant dynamics. To this effect, we propose a geometric interpretation of the system dynamics, where a scheduling policy is represented as a hybrid automaton and the scheduling problem is presented as designing a hybrid automaton. Tasks are constructed by extracting the temporal parameters of the system dynamics. We provide feasibility conditions and a lazy scheduling approach to reduce the peak power for a set of control systems. The proposed model is intuitive, scalable and effective for the large class of systems whose state-time profile can be linearly approximated.

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Real-Time and Embedded Systems Lab (mLAB)
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Suggested Citation: Nghiem, T.; Behl, M.; Pappas, G.J.; Mangharam, R.; , "Green scheduling: Scheduling of control systems for peak power reduction," Green Computing Conference and Workshops (IGCC), 2011 International , vol., no., pp.1-8, 25-28 July 2011 ©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. doi: 10.1109/IGCC.2011.6008555
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