Title MINLP-based hybrid strategy for operating mode selection of TES-backed-up refrigeration systems
Authors BEJARANO PELLICER, GUILLERMO, Rodriguez, David, Lemos, Joao M., Varga, Manuel, Ortega, Manuel G., BEJARANO PELLICER, GUILLERMO
External publication No
Means Int. J. Robust Nonlinear Control
Scope Article
Nature Científica
JCR Quartile 1
SJR Quartile 1
JCR Impact 3.50300
Area International
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85069838900&doi=10.1002%2frnc.4674&partnerID=40&md5=cfd8afb579e993a0e6a1ad4c29bc7e87
Publication date 01/01/2019
ISI 000478258700001
Scopus Id 2-s2.0-85069838900
DOI 10.1002/rnc.4674
Abstract This brief deals with the satisfaction of the daily cooling demand by a hybrid system that consists of a vapor-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 nonlinear 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 nonlinear MPC-based scheduling strategy previously developed are highlighted, regarding operating cost, ease of tuning, and ability to adapt to cooling demand variations.
Keywords mixed-integer nonlinear programming; phase change materials; refrigeration system; scheduling; thermal energy storage
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