dc.creatorDíaz Torres, Yamile
dc.creatorGullo, Paride
dc.creatorHernández Herrera, Hernán
dc.creatorTorres del Toro, Migdalia
dc.creatorReyes Calvo, Roy
dc.creatorSilva Ortega, Jorge I
dc.creatorGómez Sarduy, Julio
dc.date2023-09-26T20:25:43Z
dc.date2023-09-26T20:25:43Z
dc.date2023-04-28
dc.date.accessioned2023-10-03T19:55:02Z
dc.date.available2023-10-03T19:55:02Z
dc.identifierDíaz Torres, Y.; Gullo, P.; Hernández Herrera, H.; Torres del Toro, M.; Reyes Calvo, R.; Silva Ortega, J.I.; Gómez arduy, J. Energy Performance Comparison of a Chiller Plant Using the Conventional Staging and the Co-Design Approach in the Early Design Phase of Hotel Buildings. Energies 2023, 16, 3782. https://doi.org/10.3390/en16093782
dc.identifierhttps://hdl.handle.net/11323/10518
dc.identifier10.3390/en16093782
dc.identifier1996-1073
dc.identifierCorporación Universidad de la Costa
dc.identifierREDICUC - Repositorio CUC
dc.identifierhttps://repositorio.cuc.edu.co/
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9173285
dc.descriptionAs part of the design process of a chiller plant, one of the final stages is the energy testing of the system in relation to future operating conditions. Recent studies have suggested establishing robust solutions, but a conservative approach still prevails at this stage. However, the results of some recent studies suggest the application of a new co-design (control–design) approach. The present research involves a comparative analysis between the use of conventional staging and the co-design approach in the design phase of a chiller plant. This paper analyzes the energy consumption estimations of six different chiller plant combinations for a Cuban hotel. For the conservative approach using on/off traditional staging, the results suggest that the best option would be the adoption of a chiller plant featuring a symmetrical configuration. However, the outcomes related to the co-design approach suggest that the best option would be an asymmetrical configuration. The energy savings results were equal to 24.8% and the resulting coefficient of performance (COP) was 59.7% greater than that of the symmetrical configuration. This research lays firm foundations for the correct choice and design of a suitable chiller plant configuration for a selected hotel, allowing for significant energy savings in the tourism sector.
dc.format23 páginas
dc.formatapplication/pdf
dc.formatapplication/pdf
dc.languageeng
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)
dc.publisherSwitzerland
dc.relationEnergies
dc.relation1. Fang, X.; Jin, X.; Du, Z.; Wang, Y.; Shi, W. Evaluation of the design of chilled water system based on the optimal operation performance of equipments. Appl. Therm. Eng. 2017, 113, 435–448. [CrossRef]
dc.relation2. ASHRAE. ASHRAE Fundamentals Handbook; ASHRAE: Peachtree Corners, GA, USA, 2017; ISBN 10: 1939200598.
dc.relation3. Díaz Torres, Y.; Álvarez Guerra Plasencia, A.; Viego Felipe, P.; Crespo Sanchez, G.; Diaz Gonzalez, M. Chiller plant design. Review of the aspects that involve its efficient design. Ing. Energética 2020, 41, e1711.
dc.relation4. Taylor, S. Fundamentals of Design and Control of Central Chilled-Water Plans (I-P); Atlanta ASHRAE: Peachtree Corners, GA, USA, 2017; ISBN 978-1-939200-67-9.
dc.relation5. Cheng, Q.; Wang, S.; Yan, C. Sequential Monte Carlo simulation for robust optimal design of cooling water system with quantified uncertainty and reliability. Energy 2016, 118, 489–501. [CrossRef]
dc.relation6. Yan, C.; Cheng, Q.; Cai, H. Life-Cycle optimization of a chiller plant with quantified analysis of uncertainty and reliability in commercial buildings. Appl. Sci. 2019, 9, 1548. [CrossRef]
dc.relation7. Huang, P.; Huang, G.; Augenbroe, G.; Li, S. Optimal configuration of multiple-chiller plants under cooling load uncertainty for different climate effects and building types. Energy Build. 2018, 158, 684–697. [CrossRef]
dc.relation8. Li, H.; Wang, S.; Xiao, F. Probabilistic optimal design and on-site adaptive commissioning of building air-conditioning systems concerning uncertainties. Energy Procedia 2019, 158, 2725–2730. [CrossRef]
dc.relation9. Sun, Y.; Wang, S.; Huang, G. Chiller sequencing control with enhanced robustness for energy efficient operation. Energy Build. 2009, 41, 1246–1255. [CrossRef]
dc.relation10. Gang, W.; Wang, S.; Xiao, F.; Gao, D.-c. Robust optimal design cooling systems considering cooling load uncertainty and equipment reliability. Appl. Energy 2015, 159, 265–275. [CrossRef]
dc.relation11. Gang, W.; Wang, S.; Yan, C.; Xiao, F. Robust optimal design of building cooling systems concerning uncertainties using mini-max regret theory. Sci. Technol. Built Environ. 2015, 21, 789–799. [CrossRef]
dc.relation12. Cheng, Q.; Yan, C.; Wang, S. Robust Optimal Design of Chiller Plants Based on Cooling Load Distribution. Energy Procedia 2015, 75, 1354–1359. [CrossRef]
dc.relation13. Niu, J.; Tian, Z.; Lu, Y.; Zhao, H.; Lan, B. A robust optimization model for designing the building cooling source under cooling load uncertainty. Appl. Energy 2019, 241, 390–403. [CrossRef]
dc.relation14. Chen, Y.; Yang, C.; Pan, X.; Yan, D. Desing and operation optimization of multi-chiller plants based on energy performance simulation. Energy Build. 2020, 222, 110100. [CrossRef]
dc.relation15. Bhattacharya, A.; Vasisht, S.; Adetola, V.; Huang, S.; Sharma, H.; Vrabie, D. Control co-design of commercial building chiller plant using Bayesian optimization. Energy Build. 2021, 246, 111077. [CrossRef]
dc.relation16. Garcia-Sanz, M. Control co-design: An engineering game changer. Adv. Control. Appl. Eng. Ind. Syst. 2019, 1, e18. [CrossRef]
dc.relation17. Rampazzo, M. A static moving boundary modelling approach for simulation of indirect evaporative free cooling systems. Appl. Energy 2019, 250, 1719–1728.
dc.relation18. Masburah, R.; Sinha, S.; Lochan, R.; Dey, S.; Zhu, Q. Co-Designing Intelligent Control of Building HVAC and Microgrids. DSD 2021: Euromicro Conference on Digital System Design. 2021. Available online: https://ieeexplore.ieee.org/document/9556332 (accessed on 20 December 2021).
dc.relation19. Díaz-Torres, Y.; Calvo, R.; Herrera, H.; Gomez, S.; Guerra, M.; Silva, J. Procedure to obtain the optimal distribution cooling capacity of an air-condensed chiller plant for a hotel facility conceptual design. Energy Rep. 2021, 7, 622–637. [CrossRef]
dc.relation20. Díaz Torres, Y.R.; Hernandez, H.; Torres, M.; Alvarez-Guerra, M.; Gullo, P.; Silva, I. Statistical- mathematical procedure to determine the cooling distribution of a chiller plant. Energy Rep. 2022, 8, 512–526. [CrossRef]
dc.relation21. Thangavelu, S.R.; Myat, A.; Khambadkone, A. Energy optimization methodology of multi-chiller plant in commercial buildings. Energy 2017, 123, 64–76. [CrossRef]
dc.relation22. Díaz-Torres, Y.; Valdivia-Noda, Y.; Monteagudo-Yanes, J.P.; Miranda-Torres, Y. Application of building energy simulation in the validation of operational strategies of HVAC systems on a tropical hotel. Ing. Mecánica 2017, 20, 31–38.
dc.relation23. TRNSYS 16; Solar Energy Laboratory, University of Wisconsin-Madison: Madison, WI, USA, 2006; Volume 5, Mathematical Reference.
dc.relation24. ASHRAE 55; Thermal Environmental Conditions for Human Occupancy. ASHRAE: Washington, DC, USA, 2010.
dc.relation25. Díaz-Torres, Y.; Santana-Justiz, M.; Francisco-Pedro, G.J.; Daniel-Álvarez, L.; Miranda-Torres, Y.; Guerra-Plascencia, M.Á. Methodology for the preparation and selection of black box mathematical models for the energy simulation of screw type chillers. Ing. Mecánica 2020, 23, e612.
dc.relation26. White, H. A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica 1980, 48, 817–838. [CrossRef]
dc.relation27. Breusch, T.S.; Pagan, A. The Review of Economic Studies. In Econometrics Issue; Oxford University Press: Oxford, UK, 1980; Volume 47, pp. 239–253.
dc.relation28. Jarque, C.M.; Bera, A.K. A test for normality of observations and regression residuals. Int. Stat. Rev. 1987, 55, 163–172. [CrossRef]
dc.relation29. Catrini, P.; Piacentino, A.; Cardona, F.; Ciulla, G. Exergoeconomic analysis as support in decision-making for the design and operation of multiple chiller in air conditioning applications. Energy Convers. Manag. 2020, 220, 113051. [CrossRef]
dc.relation30. Teimourzadeh, H.; Jabari, F.; Mohammadi-Ivatloo, B. An augmented group search optimization algorithm for optimal cooling-load dispatch in multi-chiller plants. Comput. Electr. Eng. 2020, 85, 106434. [CrossRef]
dc.relation31. Ho, W.T.; Yu, F.W. Improved model and optimization for the energy performance of chiller syste with diverse component staging. Energy 2021, 217, 119376. [CrossRef]
dc.relation32. Chang, Y.-C.; Lin, F.-A.; Lin, C.H. Optimal Chillers sequencing by branch and bound method for saving energy. Energy Convers. Manag. 2005, 46, 2158–2172. [CrossRef]
dc.relation33. Witkoswski, K.; Haering, P.; Seidelt, S.; Pini, N. Role of thermal technologies for enhancing flexibility in multi-energy systems through sector coupling: Technical suitability and expected developments. IET Energy Syst. Integr. 2020, 2, 69–79. [CrossRef]
dc.relation34. Acerbi, A.; Rampazzo, M.; De Nicolao, G. Na exact algorithm for the optimal chiller loading problem and its application to the OptimalChiller Sequencing Problem. Energies 2020, 13, 6372. [CrossRef]
dc.relation35. Satué, M.; Arahal, M.; Acedo, L.; Ortega, M. Economic versus energetic model predictive control of a cold production plant with thermal energy storage. Appl. Therm. Eng. 2022, 210, 118309. [CrossRef]
dc.relation36. Qiu, S.; Zhang, W.; Li, J.; Chen, J.; Li, Z.; Li, Z. A chiller operation strategy based on multiple-objetive optimization. Energy Procedia 2018, 152, 318–323. [CrossRef]
dc.relation37. Zheng, Z.; Li, J.; Duan, P. Optimal chiller loading by improved artificial fish swarm algorithm for energy saving. Math. Comput. Simul. 2019, 155, 227–243. [CrossRef]
dc.relation38. Norma Cubana NC 217: 2002; Climatización. Especificaciones de Diseños. Temperaturas en Locales Climatizados. Norma Cubana: Havana, Cuba, 2002.
dc.relation39. Guerra, M.A.; Cabello, J.; Sousa, V.; Sagastume, A.; Monteagudo, Y.; Lapido, M.; Lara, B. Forescasting and control of the electricity consumption in hotels. In Proceedings of the IX International Conference for Renewable Energy, Energy Saving and Energy Education (CIER 2017); Centro de Estudio de Tecnologias Energeticas Renovables CETER: Havana, Cuba, 2017; p. 1CD-ROM.
dc.relation40. Valdivia, Y.; Álvarez Guerra, M.; Gómez, J.; Luc, H.; Vandecasteele, C. Sanitary hot water production from heat recovery in hotel buildings in Cuba. Ing. Energética 2019, 40, 234–244.
dc.relation41. E-View 12 Student Version. Available online: https://www.eviews.com/home.html (accessed on 14 February 2023).
dc.relation42. METEONORM, 2020. Global Meteorological Database for Engineers, Planners and Education. Available online: www.meteonorm. com/pages/en/meteonorm.php (accessed on 10 July 2022).
dc.relation43. MATLAB Simulink. 2018. Available online: https://www.mathworks.com/help/simulink/release-notes-R2018a.html (accessed on 14 February 2023).
dc.relation44. Norma Cubana NC 220-3:2009; Edificaciones-Requisitos de diseño para la eficiencia energética-Parte 3: Sistemas y Equipamiento de Calefacción, Ventilación y Aire Acondicionado. Oficina Nacional de Normalización (NC): Havana, Cuba, 2009.
dc.relation23
dc.relation1
dc.relation9
dc.relation16
dc.rights© 2023 by the authors. Licensee MDPI, Basel, Switzerland.
dc.rightsAtribución 4.0 Internacional (CC BY 4.0)
dc.rightshttps://creativecommons.org/licenses/by/4.0/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.sourcehttps://www.mdpi.com/1996-1073/16/9/3782
dc.subjectChiller plant
dc.subjectCo-design
dc.subjectTraditional staging
dc.subjectOptimal chiller loading
dc.subjectOptimal chiller sequencing
dc.titleEnergy performance comparison of a chiller plant using the conventional staging and the co-design approach in the early design phase of hotel buildings
dc.typeArtículo de revista
dc.typehttp://purl.org/coar/resource_type/c_2df8fbb1
dc.typeText
dc.typeinfo:eu-repo/semantics/article
dc.typehttp://purl.org/redcol/resource_type/ART
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typehttp://purl.org/coar/version/c_970fb48d4fbd8a85


Este ítem pertenece a la siguiente institución