2024-03-28T16:08:59Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/71272022-11-15T01:05:19Zcom_10259_4249com_10259_5086com_10259_2604com_10259_6155com_10259_4266com_10259.4_106com_10259_6164com_10259_4534col_10259_4250col_10259_6156col_10259_6165
2022-11-14T11:29:02Z
urn:hdl:10259/7127
Integrated Design of a Supermarket Refrigeration System by Means of Experimental Design Adapted to Computational Problems
Sarabia Ortiz, Daniel
Ortiz Fernández, Mª Cruz
Sarabia Peinador, Luis Antonio
Computational experiment
D-optimal
Integrated design and control
Surrogate model
Desirability
Experimental design
Hybrid Model Predictive Control
Mixture
In this paper, an integrated design of a supermarket refrigeration system has been used to obtain a process with better operability. It is formulated as a multi-objective optimization problem where control performance is evaluated by six indices and the design variables are the number and discrete power of each compressor to be installed. The functional dependence between design and performance is unknown, and therefore the optimal configuration must be obtained through a computational experimentation. This work has a double objective: to adapt the surface response methodology (SRM) to optimize problems without experimental variability as are the computational ones and show the advantage of considering the integrated design. In the SRM framework, the problem is stated as a mixture design with constraints and a synergistic cubic model where a D-optimal design is applied to perform the experiments. Finally, the multi-objective problem is reduced to a single objective one by means of a desirability function. The optimal configuration of the power distribution of the three compressors, in percentage, is (50,20,20). This solution has an excellent behaviour with respect to the six indices proposed, with a significant reduction in time oscillations of controlled variables and power consumption compared with other possible power distributions.
2022-11-14T11:29:02Z
2022-11-14T11:29:02Z
2022-11
info:eu-repo/semantics/article
1999-4893
http://hdl.handle.net/10259/7127
10.3390/a15110417
1999-4893
eng
Algorithms. 2022, V. 15, n. 11: 417
https://doi.org/10.3390/a15110417
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica, Técnica y de Innovación 2021-2023/PID2021-123654OB-C33/ES/
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
Atribución 4.0 Internacional
MDPI