  This brief deals with the satisfaction of the daily cooling demand by a
hybrid system that consists of a vapour-compression refrigeration cycle and a
thermal energy storage (TES) unit, based on phase change materials. The
addition of the TES tank to the original refrigeration plant allows to schedule
the cooling production regardless of the instantaneous demand, given that the
TES tank can store cold energy and release it whenever deemed appropriate. The
scheduling problem is posed as an optimization problem based on mixed-integer
non-linear programming (MINLP), since it includes both discrete and continuous
variables. The latter corresponds to the references on the main cooling powers
involved in the problem (cooling production at the evaporator and TES
charging/discharging), whereas the discrete variables define the operating mode
scheduling. Therefore, in addition to the hybrid features of the physical
plant, a hybrid optimal control strategy is also proposed. A receding horizon
approach is applied, similar to model predictive control (MPC) strategies,
while economic criteria are imposed in the objective function, as well as
feasibility issues. The TES state estimation is also addressed, since its
instantaneous charge ratio is not measurable. The proposed strategy is applied
in simulation to a challenging cooling demand profile and the main advantages
of the MINLP-based strategy over a non-linear MPC-based scheduling strategy
previously developed are highlighted, regarding operating cost, ease of tuning,
and ability to adapt to cooling demand variations.
