Desynchronized Model Predictive Control for Large Populations of Fans in Server Racks of Datacenters

The aim of this paper is to mitigate the problem of high power demand peak and load oscillations in the operation of a large population of thermostatically controlled loads (TCLs) operated by model predictive control (MPC) at the TCL level. Two desynchronized MPC schemes are introduced: 1) adding random delays in reference signals and 2) extra penalizations on MPC objective functions. For characterizing and validating the proposed desynchronization MPC schemes, a partial differential equation (PDE) model is developed to represent the evolution of the operational states of the TCLs controlled by MPC in a population. The focus of this paper is put on the control of cooling fans in server racks of datacenters, whereas the proposed approach is applicable to other types of TCLs. Numerical simulation studies are carried out and the obtained results confirm the validity and the applicability of the developed approach.

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