A multiparametric programming rolling horizon scheduling framework: application in a network of combined heat and power systems

Abstract

We introduce a new approach for the reactive scheduling of production systems with uncertain parameters of bounded form. The proposed method follows a state-space representation for the scheduling problem, and relies on the use of a rolling horizon framework and multiparametric programming (mp) techniques. We show that by considering as uncertain parameters the set of variables that describe the state of the system at the beginning of the prediction horizon, we can effectively formulate a set of state-space mp problems that are solved just once and offline. In contrast to existing methods, the repetitive solution of a new mp after each disruptive event is avoided. The results of the parametric optimization are used in a rolling horizon basis without the need for online optimization. The proposed mp rolling horizon (mpRH) approach is applied in the scheduling of a network of combined heat and power (CHP) units.