Evaluación energética del sistema bombeo de un esquema de climatización con enfriadoras de agua para un edificio educativo utilizando simulación dinámica

The present work is focused on energy evaluation in different configurations in a pumping system for an air conditioning scheme provided with water chiller. The study considered a building simulation software EnergyPlus V8.6, also there are considered factors that exhibit influence on building energ...

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Autores:
Balbis Morejon, Milen
Tovar Ospino, Ivan
Castro Pena, Juan Jose
Cardenas Escorcia, Yulineth del Carmen
Tipo de recurso:
Article of journal
Fecha de publicación:
2017
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
spa
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/4600
Acceso en línea:
https://hdl.handle.net/11323/4600
https://repositorio.cuc.edu.co/
Palabra clave:
Air conditioning system
Buildings efficiency
Dynamic simulation buildings
Pumping system
Sistema de climatización chiller
Sistema de bombeo
Desempeño energético
Simulación dinámica edificios
Rights
openAccess
License
Attribution-NonCommercial-ShareAlike 4.0 International
id RCUC2_a0766866fe8d83b5f51f422c2206c2cf
oai_identifier_str oai:repositorio.cuc.edu.co:11323/4600
network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.spa.fl_str_mv Evaluación energética del sistema bombeo de un esquema de climatización con enfriadoras de agua para un edificio educativo utilizando simulación dinámica
dc.title.translated.spa.fl_str_mv Energy evaluation of the pumping system of an air conditioning scheme with water chillers for an educational building using dynamic simulation
title Evaluación energética del sistema bombeo de un esquema de climatización con enfriadoras de agua para un edificio educativo utilizando simulación dinámica
spellingShingle Evaluación energética del sistema bombeo de un esquema de climatización con enfriadoras de agua para un edificio educativo utilizando simulación dinámica
Air conditioning system
Buildings efficiency
Dynamic simulation buildings
Pumping system
Sistema de climatización chiller
Sistema de bombeo
Desempeño energético
Simulación dinámica edificios
title_short Evaluación energética del sistema bombeo de un esquema de climatización con enfriadoras de agua para un edificio educativo utilizando simulación dinámica
title_full Evaluación energética del sistema bombeo de un esquema de climatización con enfriadoras de agua para un edificio educativo utilizando simulación dinámica
title_fullStr Evaluación energética del sistema bombeo de un esquema de climatización con enfriadoras de agua para un edificio educativo utilizando simulación dinámica
title_full_unstemmed Evaluación energética del sistema bombeo de un esquema de climatización con enfriadoras de agua para un edificio educativo utilizando simulación dinámica
title_sort Evaluación energética del sistema bombeo de un esquema de climatización con enfriadoras de agua para un edificio educativo utilizando simulación dinámica
dc.creator.fl_str_mv Balbis Morejon, Milen
Tovar Ospino, Ivan
Castro Pena, Juan Jose
Cardenas Escorcia, Yulineth del Carmen
dc.contributor.author.spa.fl_str_mv Balbis Morejon, Milen
Tovar Ospino, Ivan
Castro Pena, Juan Jose
Cardenas Escorcia, Yulineth del Carmen
dc.subject.spa.fl_str_mv Air conditioning system
Buildings efficiency
Dynamic simulation buildings
Pumping system
Sistema de climatización chiller
Sistema de bombeo
Desempeño energético
Simulación dinámica edificios
topic Air conditioning system
Buildings efficiency
Dynamic simulation buildings
Pumping system
Sistema de climatización chiller
Sistema de bombeo
Desempeño energético
Simulación dinámica edificios
description The present work is focused on energy evaluation in different configurations in a pumping system for an air conditioning scheme provided with water chiller. The study considered a building simulation software EnergyPlus V8.6, also there are considered factors that exhibit influence on building energy performance where they operate, such as climate, dynamic flows and thermal inertia in materials. Results showed a reduction of 3,1% of the annual energy demand in an educational building, reducing energy consumption and operating costs for a typical year of operation.
publishDate 2017
dc.date.issued.none.fl_str_mv 2017-09-01
dc.date.accessioned.none.fl_str_mv 2019-05-21T13:21:02Z
dc.date.available.none.fl_str_mv 2019-05-21T13:21:02Z
dc.type.spa.fl_str_mv Artículo de revista
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dc.identifier.issn.spa.fl_str_mv 07981015
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dc.relation.references.spa.fl_str_mv ASHRAE. (2011). ASHRAE Handbook-HVAC Applications (SI). Atlanta, USA: ASHRAE Inc. Balbis, M. (2010). Caracterización energética y ahorro de energía en instituciones educativas. Barranquilla: EduCosta. Cabello, J., Sousa, V., Sagastume, A., Guerra, M., Haeseldonckx, D., & Vandecasteele, C. (2016). Tools to improve forecasting and control of the electricity consumption in hotels. Journal of Cleaner Production, 803-812. Cheng, Q., Wang, S., & Yan, C. (2016). Robust optimal design of chilled water systems in buildings with quantified uncertainty and reliability for minimized life-cycle cost. Energy and Buildings, 159-169. Chien, T. C. (2005). Modeling packaged heat pumps in a quasi-steady state energy simulation program. Oklahoma. ENERGYPLUS. (2017). ENERGYPLUS. Obtenido de https://energyplus.net/sites/default/files/pdfs_v8.3.0/AuxiliaryPrograms.pdf. Fang, X., Jin, X., Du, Z., Wang, Y., & Shi, W. (2017). Evaluation of the design of chilled water system based on the optimal. Applied Thermal Engineering, 435-448. H. X. Zhao, F. M. (2012). A review on the prediction of building energy consumption. Renewable and Sustainable Energy Reviews, 16, 3586-3592. Hubbard, R. (19 de 11 de 2015). HPAC Engineering. Obtenido de http://hpac.com/november2011-digital-edition IEA. (2013). WORLD ENERGY OUTLOOK 2013. Kaplan, M., & Canner, P. (1992). Guidelines for energy simulation of commercial. . Portland. Bonneville Power Administration. Kim, G., Stumpf, A., & Kim, W. (2011). Analysis of an energy efficient building design through data mining approach. Automation in Construction, 37-43. Li, X. Q., Chena, Y., Spitler, J., & Fisher, D. (2009). Applicability of calculation methods for conduction transfer function of building constructions. International Journal of Thermal Sciences, 1441-1451. Liua, Z., Tana, H., Luod, D., Yud, G., Lid, J., & Lia, Z. (2017). Optimal chiller sequencing control in an office building consideringthe variation of chiller maximum cooling capacity. Energy and Buildings, 430–442. Luo, C., & Moghtaderi, B. (2010). Modelling of wall heat transfer using modified conduction transfer function, finite volume and complex Fourier analysis methods. Energy and Buildings, 605-617. Mui, K., & Wong, L. (2007). Cooling load calculations in subtropical climate. Building and Environment, 42, 2498–2504. Omar, M., AL-Rabghi, & K.AL-Johani. (1997). Utilizing transfer funtion method for hourly cooling load calculations. Energy Conversion, 38(4), 319-332. Pan, Y., Zuo, M., & Wu, G. (2009). Whole building energy simulation and energy saving potential analysis of a large public building. Journal of Building Performance Simulation, 4, 37– 47. Papakostas, K., Michopoulos, A., & Kyriakis, N. (2009). Equivalent full-load hours for estimating heating and cooling energy requirements in buildings: Greece case study. Applied Energy, 86, 757–761. Pérez-Lombard, L., Ortiz, J., Maestre, I. R., & Coronel, J. F. (2012). Constructing HVAC energy efficiency indicators. Energy and Buildings, 619–629. Qinglin, M., Jiejin, C., Hiroshi, Y., & M, M. A. (2009). Applying support vector machine to predict hourly cooling load in the building. Applied Energy, 86, 2249–2256. Rahman, M., Rasul, M., & Khan, M. (2010). Energy conservation measures in an institutional building in sub-tropical climate in Australia. Applied Energy, 2994–3004. S.N.AL-Saadi, & Z.Zhai. (2013). Modeling phase change materials embedded in building enclosure: A review. Renewable and Sustainable Energy Reviews, 21, 659–673. Shahrestani, M. A., Yao, R., & K.Cook, G. (2013). Characterising the energy performance of centralised HVAC&R systems in the UK. Energy and Buildings, 239-247. Tolga, N., Yunho, H., & Reinhard, R. (2009). Simulation comparison of VAV and VRF air conditioning systems in an existing building for the cooling season. Energy and Buildings, 1143- 1150. V.S.K.V.Harish, & Kumar, A. (2016). A review on modeling and simulation of building energy systems. RenewableandSustainableEnergyReviews, 56, 1272–1292. Wanga., F., Linb., H., Tub., W., Wanga., Y., & Huanga., Y. (2015). Energy Modeling and Chillers Sizing of HVAC System for a Hotel Building. Procedia Engineering, 1812-1818. Yu, F. W., & Chan, K. T. (2005). Energy signatures for assessing the energy performance of chillers. Energy and Buildings, 739–746. Yu, F., & Chan, K. (2007). Part load performance of air-cooled centrifugal chillers with variable speed condenser fan control. Building and Environment, 3816-3829. Zhao, H. X., & Magoulès, F. (2012). A review on the prediction of building energy consumption,. Renewable and Sustainable Energy Reviews, 3586-3592.
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spelling Balbis Morejon, MilenTovar Ospino, IvanCastro Pena, Juan JoseCardenas Escorcia, Yulineth del Carmen2019-05-21T13:21:02Z2019-05-21T13:21:02Z2017-09-0107981015https://hdl.handle.net/11323/4600Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/The present work is focused on energy evaluation in different configurations in a pumping system for an air conditioning scheme provided with water chiller. The study considered a building simulation software EnergyPlus V8.6, also there are considered factors that exhibit influence on building energy performance where they operate, such as climate, dynamic flows and thermal inertia in materials. Results showed a reduction of 3,1% of the annual energy demand in an educational building, reducing energy consumption and operating costs for a typical year of operation.El presente trabajo se centra en la evaluación energética de diferentes configuraciones de un sistema de bombeo para un esquema de climatización provisto con enfriadora por agua (Chiller). En el estudio se utilizó el software de simulación de edificios EnergyPlus V8.6 y se consideran factores que ejercen mayor influencia en el desempeño energético de los edificios cuando están en operación, como el clima, flujos dinámicos e inercia térmica de los materiales. Los resultados mostraron reducción del 3,1 % de la demanda anual de energía de un edificio educativo, logrando minimizar el consumo energético y el costo operacional para un año típico de operación.Balbis Morejon, Milen-0000-0002-8053-6651-600Tovar Ospino, Ivan-e5b58671-a29a-4284-9f44-763103d172c6-0Castro Pena, Juan Jose-c182540b-9b73-40b1-9847-1eb1301fee6e-0Cardenas Escorcia, Yulineth del Carmen-0000-0002-9841-701X-600spaEspaciosAttribution-NonCommercial-ShareAlike 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Air conditioning systemBuildings efficiencyDynamic simulation buildingsPumping systemSistema de climatización chillerSistema de bombeoDesempeño energéticoSimulación dinámica edificiosEvaluación energética del sistema bombeo de un esquema de climatización con enfriadoras de agua para un edificio educativo utilizando simulación dinámicaEnergy evaluation of the pumping system of an air conditioning scheme with water chillers for an educational building using dynamic simulationArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionASHRAE. (2011). ASHRAE Handbook-HVAC Applications (SI). Atlanta, USA: ASHRAE Inc. Balbis, M. (2010). Caracterización energética y ahorro de energía en instituciones educativas. Barranquilla: EduCosta. Cabello, J., Sousa, V., Sagastume, A., Guerra, M., Haeseldonckx, D., & Vandecasteele, C. (2016). Tools to improve forecasting and control of the electricity consumption in hotels. Journal of Cleaner Production, 803-812. Cheng, Q., Wang, S., & Yan, C. (2016). Robust optimal design of chilled water systems in buildings with quantified uncertainty and reliability for minimized life-cycle cost. Energy and Buildings, 159-169. Chien, T. C. (2005). Modeling packaged heat pumps in a quasi-steady state energy simulation program. Oklahoma. ENERGYPLUS. (2017). ENERGYPLUS. Obtenido de https://energyplus.net/sites/default/files/pdfs_v8.3.0/AuxiliaryPrograms.pdf. Fang, X., Jin, X., Du, Z., Wang, Y., & Shi, W. (2017). Evaluation of the design of chilled water system based on the optimal. Applied Thermal Engineering, 435-448. H. X. Zhao, F. M. (2012). A review on the prediction of building energy consumption. Renewable and Sustainable Energy Reviews, 16, 3586-3592. Hubbard, R. (19 de 11 de 2015). HPAC Engineering. Obtenido de http://hpac.com/november2011-digital-edition IEA. (2013). WORLD ENERGY OUTLOOK 2013. Kaplan, M., & Canner, P. (1992). Guidelines for energy simulation of commercial. . Portland. Bonneville Power Administration. Kim, G., Stumpf, A., & Kim, W. (2011). Analysis of an energy efficient building design through data mining approach. Automation in Construction, 37-43. Li, X. Q., Chena, Y., Spitler, J., & Fisher, D. (2009). Applicability of calculation methods for conduction transfer function of building constructions. International Journal of Thermal Sciences, 1441-1451. Liua, Z., Tana, H., Luod, D., Yud, G., Lid, J., & Lia, Z. (2017). Optimal chiller sequencing control in an office building consideringthe variation of chiller maximum cooling capacity. Energy and Buildings, 430–442. Luo, C., & Moghtaderi, B. (2010). Modelling of wall heat transfer using modified conduction transfer function, finite volume and complex Fourier analysis methods. Energy and Buildings, 605-617. Mui, K., & Wong, L. (2007). Cooling load calculations in subtropical climate. Building and Environment, 42, 2498–2504. Omar, M., AL-Rabghi, & K.AL-Johani. (1997). Utilizing transfer funtion method for hourly cooling load calculations. Energy Conversion, 38(4), 319-332. Pan, Y., Zuo, M., & Wu, G. (2009). Whole building energy simulation and energy saving potential analysis of a large public building. Journal of Building Performance Simulation, 4, 37– 47. Papakostas, K., Michopoulos, A., & Kyriakis, N. (2009). Equivalent full-load hours for estimating heating and cooling energy requirements in buildings: Greece case study. Applied Energy, 86, 757–761. Pérez-Lombard, L., Ortiz, J., Maestre, I. R., & Coronel, J. F. (2012). Constructing HVAC energy efficiency indicators. Energy and Buildings, 619–629. Qinglin, M., Jiejin, C., Hiroshi, Y., & M, M. A. (2009). Applying support vector machine to predict hourly cooling load in the building. Applied Energy, 86, 2249–2256. Rahman, M., Rasul, M., & Khan, M. (2010). Energy conservation measures in an institutional building in sub-tropical climate in Australia. Applied Energy, 2994–3004. S.N.AL-Saadi, & Z.Zhai. (2013). Modeling phase change materials embedded in building enclosure: A review. Renewable and Sustainable Energy Reviews, 21, 659–673. Shahrestani, M. A., Yao, R., & K.Cook, G. (2013). Characterising the energy performance of centralised HVAC&R systems in the UK. Energy and Buildings, 239-247. Tolga, N., Yunho, H., & Reinhard, R. (2009). Simulation comparison of VAV and VRF air conditioning systems in an existing building for the cooling season. Energy and Buildings, 1143- 1150. V.S.K.V.Harish, & Kumar, A. (2016). A review on modeling and simulation of building energy systems. RenewableandSustainableEnergyReviews, 56, 1272–1292. Wanga., F., Linb., H., Tub., W., Wanga., Y., & Huanga., Y. (2015). Energy Modeling and Chillers Sizing of HVAC System for a Hotel Building. Procedia Engineering, 1812-1818. Yu, F. W., & Chan, K. T. (2005). Energy signatures for assessing the energy performance of chillers. Energy and Buildings, 739–746. Yu, F., & Chan, K. (2007). Part load performance of air-cooled centrifugal chillers with variable speed condenser fan control. Building and Environment, 3816-3829. Zhao, H. X., & Magoulès, F. (2012). A review on the prediction of building energy consumption,. 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