| Title |
Energy Management of Refrigeration Systems with Thermal Energy Storage Based on Non-Linear Model Predictive Control |
| Authors |
BEJARANO PELLICER, GUILLERMO, Lemos, Joao M. , Rico-Azagra, Javier , Rubio, Francisco R. , Ortega, Manuel G. |
| External publication |
No |
| Means |
Mathematics |
| Scope |
Article |
| Nature |
Científica |
| JCR Quartile |
1 |
| SJR Quartile |
2 |
| JCR Impact |
2.40000 |
| SJR Impact |
0.44600 |
| Web |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137763269&doi=10.3390%2fmath10173167&partnerID=40&md5=02237ce3f6e4b75588025ccc11bba1ca |
| Publication date |
01/09/2022 |
| ISI |
000851981400001 |
| Scopus Id |
2-s2.0-85137763269 |
| DOI |
10.3390/math10173167 |
| Abstract |
This work addresses the energy management of a combined system consisting of a refrigeration cycle and a thermal energy storage tank based on phase change materials. The storage tank is used as a cold-energy buffer, thus decoupling cooling demand and production, which leads to cost reduction and satisfaction of peak demand that would be infeasible for the original cycle. A layered scheduling and control strategy is proposed, where a non-linear predictive scheduler computes the references of the main powers involved (storage tank charging/discharging powers and direct cooling production), while a low-level controller ensures that the requested powers are actually achieved. A simplified model retaining the dominant dynamics is proposed as the prediction model for the scheduler. Economic, efficiency, and feasibility criteria are considered, seeking operating cost reduction while ensuring demand satisfaction. The performance of the proposed strategy for the system with energy storage is compared in simulation with that of a cycle without energy storage, where the former is shown to satisfy challenging demands while reducing the operating cost by up to 28%. The proposed approach also shows suitable robustness when significant uncertainty in the prediction model is considered. |
| Keywords |
refrigeration system; thermal energy storage; phase change materials; non-linear model predictive control; scheduling |
| Universidad Loyola members |
|
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