Energy evaluation and energy savings analysis with the 2 selection of AC systems in an educational building

This paper presents an energy performance assessment on an educational building in Barranquilla, Colombia. The electricity consumption performance was assessed using the software DesignBuilder for two different Air Conditioning (AC) systems. The current electricity intensity is 215.3 kWh/m2 -year an...

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Autores:
BALBIS MOREJON, MILEN
Cabello Eras, Juan José
Rey-Martínez, Francisco Javier
Rey Hernandez, Javier M
Tipo de recurso:
Article of journal
Fecha de publicación:
2021
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/8579
Acceso en línea:
https://hdl.handle.net/11323/8579
https://doi.org/10.3390/su13147527
https://repositorio.cuc.edu.co/
Palabra clave:
Energy efficiency indicators
HVAC systems
Energy savings
Life-cycle cost
Building energy
Indicadores de eficiencia energética
Sistemas de climatización
Ahorros de energía
El costo del ciclo de vida
Energía del edificio
Rights
openAccess
License
CC0 1.0 Universal
id RCUC2_d6760eff43116fbe85d5bd62c4dd3e75
oai_identifier_str oai:repositorio.cuc.edu.co:11323/8579
network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.spa.fl_str_mv Energy evaluation and energy savings analysis with the 2 selection of AC systems in an educational building
title Energy evaluation and energy savings analysis with the 2 selection of AC systems in an educational building
spellingShingle Energy evaluation and energy savings analysis with the 2 selection of AC systems in an educational building
Energy efficiency indicators
HVAC systems
Energy savings
Life-cycle cost
Building energy
Indicadores de eficiencia energética
Sistemas de climatización
Ahorros de energía
El costo del ciclo de vida
Energía del edificio
title_short Energy evaluation and energy savings analysis with the 2 selection of AC systems in an educational building
title_full Energy evaluation and energy savings analysis with the 2 selection of AC systems in an educational building
title_fullStr Energy evaluation and energy savings analysis with the 2 selection of AC systems in an educational building
title_full_unstemmed Energy evaluation and energy savings analysis with the 2 selection of AC systems in an educational building
title_sort Energy evaluation and energy savings analysis with the 2 selection of AC systems in an educational building
dc.creator.fl_str_mv BALBIS MOREJON, MILEN
Cabello Eras, Juan José
Rey-Martínez, Francisco Javier
Rey Hernandez, Javier M
dc.contributor.author.spa.fl_str_mv BALBIS MOREJON, MILEN
Cabello Eras, Juan José
Rey-Martínez, Francisco Javier
Rey Hernandez, Javier M
dc.subject.spa.fl_str_mv Energy efficiency indicators
HVAC systems
Energy savings
Life-cycle cost
Building energy
Indicadores de eficiencia energética
Sistemas de climatización
Ahorros de energía
El costo del ciclo de vida
Energía del edificio
topic Energy efficiency indicators
HVAC systems
Energy savings
Life-cycle cost
Building energy
Indicadores de eficiencia energética
Sistemas de climatización
Ahorros de energía
El costo del ciclo de vida
Energía del edificio
description This paper presents an energy performance assessment on an educational building in Barranquilla, Colombia. The electricity consumption performance was assessed using the software DesignBuilder for two different Air Conditioning (AC) systems. The current electricity intensity is 215.3 kWh/m2 -year and centralized AC systems with individual fan coils and a water chiller share 66% of the total consumption and lighting at 16%. The simulation of the AC technology change to Variable Refrigerant Flow (VRF) resulted in an improvement of 38% in AC energy intensity with 88 kWh/m2 -year and significant savings in electricity consumption and life-cycle cost of AC systems in buildings.
publishDate 2021
dc.date.accessioned.none.fl_str_mv 2021-08-23T15:50:25Z
dc.date.available.none.fl_str_mv 2021-08-23T15:50:25Z
dc.date.issued.none.fl_str_mv 2021-07-06
dc.type.spa.fl_str_mv Artículo de revista
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.content.spa.fl_str_mv Text
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/article
dc.type.redcol.spa.fl_str_mv http://purl.org/redcol/resource_type/ART
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/acceptedVersion
format http://purl.org/coar/resource_type/c_6501
status_str acceptedVersion
dc.identifier.issn.spa.fl_str_mv 20711050
dc.identifier.uri.spa.fl_str_mv https://hdl.handle.net/11323/8579
dc.identifier.doi.spa.fl_str_mv https://doi.org/10.3390/su13147527
dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
dc.identifier.reponame.spa.fl_str_mv REDICUC - Repositorio CUC
dc.identifier.repourl.spa.fl_str_mv https://repositorio.cuc.edu.co/
identifier_str_mv 20711050
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url https://hdl.handle.net/11323/8579
https://doi.org/10.3390/su13147527
https://repositorio.cuc.edu.co/
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.references.spa.fl_str_mv 1. De Gastines, M.; Correa, E.; Pattini, A. Heat Transfer Through Window Frames in Energyplus: Model Evaluation and Improvement. Adv. Build. Energy Res. 2019, 13, 138–155. [CrossRef]
2. Shahrestani, M.; Yao, R.; Cook, G.K. A Fuzzy Multiple Attribute Decision Making Tool For Hvac&R Systems Selection with Considering the Future Probabilistic Climate Changes And Electricity Decarbonisation Plans in The Uk. Energy Build. 2018, 159, 398–418. [CrossRef]
3. Wang, S.; Yan, C.; Xiao, F. Quantitative Energy Performance Assessment Methods for Existing Buildings. Energy Build. 2012, 55, 873–888. [CrossRef]
4. Indicative Energy Efficiency Action Plan 2017–2022. Available online: http://extwprlegs1.fao.org/docs/pdf/col181199.pdf (accessed on 30 June 2021). (In Spanish).
5. Unidad De Planeación Minero Energética. Plan Energético Nacional Colombia: Ideario Energético 2050, Unidad Planeación Min. Energética; Upme: Bogotá, Colombia, 2015. Available online: https://www1.upme.gov.co/documents/pen_idearioenergetico205 0.pdf (accessed on 12 February 2021). (In Spanish)
6. Pérez-Lombard, L.; Ortiz, J.; Pout, C. A Review on Buildings Energy Consumption Information. Energy Build. 2008, 40, 394–398. [CrossRef]
7. Poel, B.; Van Cruchten, G.; Balaras, C.A. Energy Performance Assessment of Existing Dwellings. Energy Build. 2007, 39, 393–403. [CrossRef]
8. Nikolaou, T.; Kolokotsa, D.; Stavrakakis, G. Review on Methodologies for Energy Benchmarking, Rating and Classification of Buildings. Adv. Build. Energy Res. 2011, 5, 53–70. [CrossRef]
9. Brambley, M.R.; Hansen, D.; Haves, P.; Holmberg, D.R.; Mcdonald, S.C.; Roth, K.W.; Torcellini, P. Advanced Sensors and Controls For Building Applications: Market Assessment and Potential R&D Pathways. Pac. Northwest Natl. Lab. 2005, 162. [CrossRef]
10. Luo, R.; Han, Y.; Zhou, X. Characteristics of Campus Energy Consumption in North China of Science and Technology Ruijiang. Procedia Eng. 2017, 205, 3816–3823. [CrossRef]
11. Alajmi, A. Energy Audit of An Educational Building in A Hot Summer Climate. Energy Build. 2012, 47, 122–130. [CrossRef]
12. Xia, J.; Hong, T.; Shen, Q.; Feng, W.; Yang, L.; Im, P.; Lu, A.; Bhandari, M. Comparison of Building Energy Use Data between the United States and China. Energy Build. 2014, 78, 165–175. [CrossRef]
13. Afroz, Z.; Higgins, G.; Urmee, T.; Shafiullah, G. Technological Advancement of Energy Management Facility of Institutional Buildings: A Case Study. Energy Procedia 2017, 142, 3088–3095. [CrossRef]
14. Madrigal, J.A.; Cabello, J.J.; Sagastume, A.; Balbis, M. Evaluation of Air Conditioning in Commercial Buildings, Integrating Thermography Techniques, Simulation and Modeling. Inf. Tecnol. 2018, 29, 179–188. [CrossRef]
15. Aryal, A.; Becerik-Gerber, B. Energy Consequences of Comfort-Driven Temperature Setpoints in Office Buildings. Energy Build. 2018, 177, 33–46. [CrossRef]
17. Balbis-Morejon, M.; Tovar-Ospino, I.; Castro-Peña, J.J.; Cárdenas-Escorcia, Y.D.C. Energy assessment of the system pumping a climate control scheme with water coolers for an educational building using dynamic simulation. Espacios 2017, 38, 19–32.
18. Kim, D.; Cox, S.J.; Cho, H.; Im, P. Evaluation of Energy Savings Potential of Variable Refrigerant Flow (Vrf) from Variable Air Volume (Vav) in the U.S. Climate Locations. Energy Rep. 2017, 3, 85–93. [CrossRef]
19. Aynur, T.N.; Hwang, Y.; Radermacher, R. Simulation Comparison of Vav and Vrf Air Conditioning Systems in an Existing Building for The Cooling Season. Energy Build. 2009, 41, 1143–1150. [CrossRef]
20. Barros-Alvarez, M.; Balbis-Morejon, M.; Tovar-Ospino, I.; Castro-Peña, J.J.; De Leon-Siado, L.; Silva-Ortega, J.I.; Rosales Villa, D.E. Energy Consumption Comparison Between Air Conditioning System Mini-Split and Variable Refrigerant Flow in an Educational Building. Espacios 2017, 38, 19–32.
21. Zhu, Y.; Jin, X.; Fang, X.; Du, Z. Optimal Control of Combined Air Conditioning System with Variable Refrigerant Flow and Variable Air Volume for Energy Saving. Int. J. Refrig. 2014, 42, 14–25. [CrossRef]
22. Sekki, T.; Airaksinen, M.; Saari, A. Impact of Building Usage and Occupancy on Energy Consumption in Finnish Daycare and School Buildings. Energy Build. 2015, 105, 247–257. [CrossRef]
23. Montoya, P.; Morejón, J.L.; Inga, E. Maximum Coverage of Wireless Sensor Networks for an Energy Management System in Smart Homes. INGE CUC 2016, 12, 68–78. [CrossRef]
24. Kolokotsa, D.; Gobakis, K.; Papantoniou, S.; Georgatou, C.; Kampelis, N.; Kalaitzakis, K.; Vasilakopoulou, K.; Santamouris, M. Development of A Web Based Energy Management System for University Campuses: The Camp-It Platform. Energy Build. 2016, 123, 119–135. [CrossRef]
25. Rey Martínez, J.M.; Fancisco, J.; Velazco Gómez, E.; Hernández, R. Eficiencia Energética De Los Edificios, 1st ed.; Paraninfo Sa: Madrid, España, 2018. (In Spanish)
26. Gavilán, A. Análisis Comparativo De La Eficiencia Energética En Edificios Existentes Con Diferentes Herramientas De Simulación Energética. Doctoral Thesis, University of Valladolid, Valladolid, Spain, 2015.
27. Harish, V.; Kumar, A. A Review on Modeling and Simulation of Building Energy Systems. Renew. Sustain. Energy Rev. 2016, 56, 1272–1292. [CrossRef]
28. Zhao, H.X.; Magoulès, F. A Review on the Prediction of Building Energy Consumption. Renew. Sustain. Energy Rev. 2012, 16, 3586–3592. [CrossRef]
29. Strack, J.L.; Siárez, J.A.; Di Mauro, G.F.; Jacob, S.B. Impacto De La Iluminación Residencial Eficiente En La Calidad De La Energía De Una Red De Distribución. Inge Cuc 2014, 10, 9–19. (In Spanish)
30. Pérez-Lombard, L.; Ortiz, J.; Coronel, J.F.; Maestre, I.R. A Review of Hvac Systems Requirements in Building Energy Regulations. Energy Build. 2011, 43, 255–268. [CrossRef]
31. Pérez-Lombard, L.; Ortiz, J.; Maestre, I.R.; Coronel, J.F. Constructing Hvac Energy Efficiency Indicators. Energy Build. 2012, 47, 619–629. [CrossRef]
32. Fumo, N.; Mago, P.; Luck, R. Methodology to Estimate Building Energy Consumption Using Energyplus Benchmark Models. Energy Build. 2010, 42, 2331–2337. [CrossRef]
33. Papakostas, K.T.; Michopoulos, A.K.; Kyriakis, N.A. Equivalent Full-Load Hours for Estimating Heating and Cooling Energy Requirements in Buildings: Greece Case Study. Appl. Energy 2009, 86, 757–761. [CrossRef]
34. Li, Q.; Meng, Q.; Cai, J.; Yoshino, H.; Mochida, A. Applying Support Vector Machine to Predict Hourly Cooling Load in the Building. Appl. Energy 2009, 86, 2249–2256. [CrossRef]
35. Mui, K.W.; Wong, L.T.; Wai, M.K. Cooling Load Calculations in Subtropical Climate. Build. Environ. 2007, 42, 2498–2504. [CrossRef]
36. Al-Rabghi, O.M.A.; Al-Johani, K.M. Utilizing transfer function method for hourly cooling load calculations. Energy Convers. Manag. 1997, 38, 319–332. [CrossRef]
37. Victorio, D.; Raúl, B. Acondicionamiento Térmico De Edificios, 1st ed.; Juan O’Gorman Librerias: Buenos Aires, Argentina, 2005. (In Spanish)
38. Stephens, B. The Impacts of Duct Design on Life Cycle Costs of Central Residential Heating and Air-Conditioning Systems. Energy Build. 2014, 82, 563–579. (In Spanish) [CrossRef]
39. Balbis-Morejón, M.; Rey-Hernández, J.M.; Amaris-Castilla, C.; Velasco-Gómez, E.; San José-Alonso, J.F.; Rey-Martínez, F.J. Experimental Study and Analysis of Thermal Comfort in a University Campus Building in Tropical Climate. Sustainability 2020, 12, 8886. [CrossRef]
40. Balbis-Morejón, M.; Noya-Sambrano, A. Thermal Comfort Evaluation in an Educational Building with Air Conditioning Located in the Warm Tropical Climate of Colombia. IOP Conf. Ser. Mater. Sci. Eng. 2020, 844, 844. [CrossRef]
41. Ma, H.; Lai, J.; Li, C.; Yang, F.; Lai, J.; Li, C. Analysis Of School Building Energy Consumption in Tianjin, China. Energy Procedia 2019, 158, 3476–3481. [CrossRef]
42. Unidad De Planeacion Minero Energetica. Inflación De Energía En Colombia; Upme: Bogotá, Colombia, 2021. Available online: http: //www1.upme.gov.co/demandaenergetica/informe_inflacion_energia_dic_2020.pdf (accessed on 12 April 2021). (In Spanish)
43. Shahrestani, M.; Yao, R.; Cook, G.K. Decision Making for Hvac&R System Selection for a Typical Office Building in the UK. Ashrae Trans. 2012, 118, 222–229.
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spelling BALBIS MOREJON, MILENCabello Eras, Juan JoséRey-Martínez, Francisco JavierRey Hernandez, Javier M2021-08-23T15:50:25Z2021-08-23T15:50:25Z2021-07-0620711050https://hdl.handle.net/11323/8579https://doi.org/10.3390/su13147527Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/This paper presents an energy performance assessment on an educational building in Barranquilla, Colombia. The electricity consumption performance was assessed using the software DesignBuilder for two different Air Conditioning (AC) systems. The current electricity intensity is 215.3 kWh/m2 -year and centralized AC systems with individual fan coils and a water chiller share 66% of the total consumption and lighting at 16%. The simulation of the AC technology change to Variable Refrigerant Flow (VRF) resulted in an improvement of 38% in AC energy intensity with 88 kWh/m2 -year and significant savings in electricity consumption and life-cycle cost of AC systems in buildings.Este artículo presenta una evaluación del desempeño energético en un edificio educativo en Barranquilla, Colombia. El rendimiento del consumo de electricidad se evaluó mediante el software DesignBuilder para dos sistemas de aire acondicionado (AC) diferentes. La intensidad actual de la electricidad es 215,3 kWh / m2-año y sistemas de aire acondicionado centralizados con fan coils individuales y un enfriador de agua compartido 66% del consumo total e iluminación al 16%. La simulación de la tecnología AC cambia a El flujo de refrigerante variable (VRF) resultó en una mejora del 38% en la intensidad de energía de CA con 88 kWh / m2 al año y ahorros significativos en el consumo de electricidad y el costo del ciclo de vida de los sistemas de CA en edificios.BALBIS MOREJON, MILEN-will be generated-orcid-0000-0002-8053-6651-600Cabello Eras, Juan José-will be generated-orcid-0000-0003-0949-0862-600Rey-Martínez, Francisco Javier-will be generated-orcid-0000-0002-4539-239X-600Rey Hernandez, Javier M-will be generated-orcid-0000-0002-3305-6292-600application/pdfengSustainabilityCC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Sustainabilityhttps://www.mdpi.com/2071-1050/13/14/7527Energy efficiency indicatorsHVAC systemsEnergy savingsLife-cycle costBuilding energyIndicadores de eficiencia energéticaSistemas de climatizaciónAhorros de energíaEl costo del ciclo de vidaEnergía del edificioEnergy evaluation and energy savings analysis with the 2 selection of AC systems in an educational buildingArtículo 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/acceptedVersion1. De Gastines, M.; Correa, E.; Pattini, A. Heat Transfer Through Window Frames in Energyplus: Model Evaluation and Improvement. Adv. Build. Energy Res. 2019, 13, 138–155. [CrossRef]2. Shahrestani, M.; Yao, R.; Cook, G.K. A Fuzzy Multiple Attribute Decision Making Tool For Hvac&R Systems Selection with Considering the Future Probabilistic Climate Changes And Electricity Decarbonisation Plans in The Uk. Energy Build. 2018, 159, 398–418. [CrossRef]3. Wang, S.; Yan, C.; Xiao, F. Quantitative Energy Performance Assessment Methods for Existing Buildings. Energy Build. 2012, 55, 873–888. [CrossRef]4. Indicative Energy Efficiency Action Plan 2017–2022. Available online: http://extwprlegs1.fao.org/docs/pdf/col181199.pdf (accessed on 30 June 2021). (In Spanish).5. Unidad De Planeación Minero Energética. Plan Energético Nacional Colombia: Ideario Energético 2050, Unidad Planeación Min. Energética; Upme: Bogotá, Colombia, 2015. Available online: https://www1.upme.gov.co/documents/pen_idearioenergetico205 0.pdf (accessed on 12 February 2021). (In Spanish)6. Pérez-Lombard, L.; Ortiz, J.; Pout, C. A Review on Buildings Energy Consumption Information. Energy Build. 2008, 40, 394–398. [CrossRef]7. Poel, B.; Van Cruchten, G.; Balaras, C.A. Energy Performance Assessment of Existing Dwellings. Energy Build. 2007, 39, 393–403. [CrossRef]8. Nikolaou, T.; Kolokotsa, D.; Stavrakakis, G. Review on Methodologies for Energy Benchmarking, Rating and Classification of Buildings. Adv. Build. Energy Res. 2011, 5, 53–70. [CrossRef]9. Brambley, M.R.; Hansen, D.; Haves, P.; Holmberg, D.R.; Mcdonald, S.C.; Roth, K.W.; Torcellini, P. Advanced Sensors and Controls For Building Applications: Market Assessment and Potential R&D Pathways. Pac. Northwest Natl. Lab. 2005, 162. [CrossRef]10. Luo, R.; Han, Y.; Zhou, X. Characteristics of Campus Energy Consumption in North China of Science and Technology Ruijiang. Procedia Eng. 2017, 205, 3816–3823. [CrossRef]11. Alajmi, A. Energy Audit of An Educational Building in A Hot Summer Climate. Energy Build. 2012, 47, 122–130. [CrossRef]12. Xia, J.; Hong, T.; Shen, Q.; Feng, W.; Yang, L.; Im, P.; Lu, A.; Bhandari, M. Comparison of Building Energy Use Data between the United States and China. Energy Build. 2014, 78, 165–175. [CrossRef]13. Afroz, Z.; Higgins, G.; Urmee, T.; Shafiullah, G. Technological Advancement of Energy Management Facility of Institutional Buildings: A Case Study. Energy Procedia 2017, 142, 3088–3095. [CrossRef]14. Madrigal, J.A.; Cabello, J.J.; Sagastume, A.; Balbis, M. Evaluation of Air Conditioning in Commercial Buildings, Integrating Thermography Techniques, Simulation and Modeling. Inf. Tecnol. 2018, 29, 179–188. [CrossRef]15. Aryal, A.; Becerik-Gerber, B. Energy Consequences of Comfort-Driven Temperature Setpoints in Office Buildings. Energy Build. 2018, 177, 33–46. [CrossRef]17. Balbis-Morejon, M.; Tovar-Ospino, I.; Castro-Peña, J.J.; Cárdenas-Escorcia, Y.D.C. Energy assessment of the system pumping a climate control scheme with water coolers for an educational building using dynamic simulation. Espacios 2017, 38, 19–32.18. Kim, D.; Cox, S.J.; Cho, H.; Im, P. Evaluation of Energy Savings Potential of Variable Refrigerant Flow (Vrf) from Variable Air Volume (Vav) in the U.S. Climate Locations. Energy Rep. 2017, 3, 85–93. [CrossRef]19. Aynur, T.N.; Hwang, Y.; Radermacher, R. Simulation Comparison of Vav and Vrf Air Conditioning Systems in an Existing Building for The Cooling Season. Energy Build. 2009, 41, 1143–1150. [CrossRef]20. Barros-Alvarez, M.; Balbis-Morejon, M.; Tovar-Ospino, I.; Castro-Peña, J.J.; De Leon-Siado, L.; Silva-Ortega, J.I.; Rosales Villa, D.E. Energy Consumption Comparison Between Air Conditioning System Mini-Split and Variable Refrigerant Flow in an Educational Building. Espacios 2017, 38, 19–32.21. Zhu, Y.; Jin, X.; Fang, X.; Du, Z. Optimal Control of Combined Air Conditioning System with Variable Refrigerant Flow and Variable Air Volume for Energy Saving. Int. J. Refrig. 2014, 42, 14–25. [CrossRef]22. Sekki, T.; Airaksinen, M.; Saari, A. Impact of Building Usage and Occupancy on Energy Consumption in Finnish Daycare and School Buildings. Energy Build. 2015, 105, 247–257. [CrossRef]23. Montoya, P.; Morejón, J.L.; Inga, E. Maximum Coverage of Wireless Sensor Networks for an Energy Management System in Smart Homes. INGE CUC 2016, 12, 68–78. [CrossRef]24. Kolokotsa, D.; Gobakis, K.; Papantoniou, S.; Georgatou, C.; Kampelis, N.; Kalaitzakis, K.; Vasilakopoulou, K.; Santamouris, M. Development of A Web Based Energy Management System for University Campuses: The Camp-It Platform. Energy Build. 2016, 123, 119–135. [CrossRef]25. Rey Martínez, J.M.; Fancisco, J.; Velazco Gómez, E.; Hernández, R. Eficiencia Energética De Los Edificios, 1st ed.; Paraninfo Sa: Madrid, España, 2018. (In Spanish)26. Gavilán, A. Análisis Comparativo De La Eficiencia Energética En Edificios Existentes Con Diferentes Herramientas De Simulación Energética. Doctoral Thesis, University of Valladolid, Valladolid, Spain, 2015.27. Harish, V.; Kumar, A. A Review on Modeling and Simulation of Building Energy Systems. Renew. Sustain. Energy Rev. 2016, 56, 1272–1292. [CrossRef]28. Zhao, H.X.; Magoulès, F. A Review on the Prediction of Building Energy Consumption. Renew. Sustain. Energy Rev. 2012, 16, 3586–3592. [CrossRef]29. Strack, J.L.; Siárez, J.A.; Di Mauro, G.F.; Jacob, S.B. Impacto De La Iluminación Residencial Eficiente En La Calidad De La Energía De Una Red De Distribución. Inge Cuc 2014, 10, 9–19. (In Spanish)30. Pérez-Lombard, L.; Ortiz, J.; Coronel, J.F.; Maestre, I.R. A Review of Hvac Systems Requirements in Building Energy Regulations. Energy Build. 2011, 43, 255–268. [CrossRef]31. Pérez-Lombard, L.; Ortiz, J.; Maestre, I.R.; Coronel, J.F. Constructing Hvac Energy Efficiency Indicators. Energy Build. 2012, 47, 619–629. [CrossRef]32. Fumo, N.; Mago, P.; Luck, R. Methodology to Estimate Building Energy Consumption Using Energyplus Benchmark Models. Energy Build. 2010, 42, 2331–2337. [CrossRef]33. Papakostas, K.T.; Michopoulos, A.K.; Kyriakis, N.A. Equivalent Full-Load Hours for Estimating Heating and Cooling Energy Requirements in Buildings: Greece Case Study. Appl. Energy 2009, 86, 757–761. [CrossRef]34. Li, Q.; Meng, Q.; Cai, J.; Yoshino, H.; Mochida, A. Applying Support Vector Machine to Predict Hourly Cooling Load in the Building. Appl. Energy 2009, 86, 2249–2256. [CrossRef]35. Mui, K.W.; Wong, L.T.; Wai, M.K. Cooling Load Calculations in Subtropical Climate. Build. Environ. 2007, 42, 2498–2504. [CrossRef]36. Al-Rabghi, O.M.A.; Al-Johani, K.M. Utilizing transfer function method for hourly cooling load calculations. Energy Convers. Manag. 1997, 38, 319–332. [CrossRef]37. Victorio, D.; Raúl, B. 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