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In this work, a composite economic model predictive control (CEMPC) isproposed for the optimal operation of a stand-alone integrated energy system(IES). Time-scale multiplicity exists in IESs dynamics is taken into accountand addressed using multi-time-scale decomposition. The entire IES isdecomposed into three reduced-order subsystems with slow, medium, and fastdynamics. Subsequently, the CEMPC, which includes slow economic modelpredictive control (EMPC), medium EMPC and fast EMPC, is developed. The EMPCscommunicate with each other to ensure consistency in decision-making. In theslow EMPC, the global control objectives are optimized, and the manipulatedinputs explicitly affecting the slow dynamics are applied. The medium EMPCoptimizes the control objectives correlated with the medium dynamics andapplies the corresponding optimal medium inputs to the IES, while the fast EMPCoptimizes the fast dynamics relevant objectives and makes a decision on themanipulated inputs directly associated with the fast dynamics. Meanwhile,thermal comfort is integrated into the CEMPC in the form of zone tracking ofthe building temperature for achieving more control degrees of freedom toprioritize satisfying the electric demand and reducing operating costs of theIES. Moreover, a long-term EMPC based on a simplified slow subsystem model isdeveloped and incorporated into the CEMPC to ensure that the operating stateaccommodates long-term forecasts for external conditions. Finally, theeffectiveness and superiority of the proposed method are demonstrated viasimulations and a comparison with a hierarchical real-time optimizationmechanism.

Economic model predictive control of integrated energy systems: A multi-time-scale framework