Título Energy Management of Refrigeration Systems with Thermal Energy Storage Based on Non-Linear Model Predictive Control
Autores BEJARANO PELLICER, GUILLERMO, Lemos, Joao M. , Rico-Azagra, Javier , Rubio, Francisco R. , Ortega, Manuel G.
Publicación externa No
Medio Mathematics
Alcance Article
Naturaleza Científica
Cuartil JCR 1
Cuartil SJR 2
Impacto JCR 2.4
Impacto SJR 0.446
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137763269&doi=10.3390%2fmath10173167&partnerID=40&md5=02237ce3f6e4b75588025ccc11bba1ca
Fecha de publicacion 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.
Palabras clave refrigeration system; thermal energy storage; phase change materials; non-linear model predictive control; scheduling
Miembros de la Universidad Loyola

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