Procena budućih potreba za grejanjem osnovne škole korišćenjem CMIP6 klimatskih modela za 2050. i 2080. godinu
##plugins.themes.bootstrap3.article.sidebar##
Objavljeno
Feb 18, 2026
##plugins.themes.bootstrap3.article.main##
Vladan Jovanović
http://orcid.org/0009-0002-8564-9900
Marko Ignjatović
http://orcid.org/0000-0001-7205-7987
Mirko Stojiljković
http://orcid.org/0000-0003-2256-1645
Milica Tasić
http://orcid.org/0009-0001-9160-6379
Ivan Popović
http://orcid.org/0000-0003-4816-3063
http://orcid.org/0009-0002-8564-9900
Marko Ignjatović
http://orcid.org/0000-0001-7205-7987
Mirko Stojiljković
http://orcid.org/0000-0003-2256-1645
Milica Tasić
http://orcid.org/0009-0001-9160-6379
Ivan Popović
http://orcid.org/0000-0003-4816-3063
Apstrakt
Ova studija analizira buduće potrebe za grejanjem i hlađenjem u zgradi osnovne škole u Nišu, koristeći projektovane vremenske podatke u EPW formatu za godine 2050. i 2080. Vremenski podaci su generisani primenom metode EPW morphing na osnovu projekcija klimatskih modela CMIP6, uključujući CNRM-CM6.1-HR, EC-Earth3 i EC-Earth3-Veg, pod različitim scenarijima emisija (SSP1-2.6, SSP2-4.5, SSP3-7.0 i SSP5-8.5). Korišćenjem ovih podataka sprovedene su energetske simulacije za procenu godišnje potrošnje energije za grejanje i analizu perioda visokih temperatura relevantnih za potrebe hlađenja, uzimajući u obzir dinamiku prisustva učenika i osoblja, unutrašnje toplotne dobitke i postojeće režime korišćenja. Cilj istraživanja je da se identifikuju potencijalne promene u energetskim zahtevima školskih objekata usled klimatskih promena i pruže preporuke za prilagođavanje sistema grejanja i hlađenja u skladu sa očekivanim klimatskim uslovima sredinom i krajem 21. veka. Rezultati pokazuju značajne razlike među modelima i scenarijima, posebno u periodima visokih temperatura, što naglašava važnost korišćenja više modela i metodološki konzistentnog pristupa pri planiranju energetski efikasnih i klimatski adaptiranih obrazovnih objekata..
##plugins.themes.bootstrap3.article.details##
Kako citirati
JOVANOVIĆ, Vladan et al.
Procena budućih potreba za grejanjem osnovne škole korišćenjem CMIP6 klimatskih modela za 2050. i 2080. godinu.
Zbornik Međunarodnog kongresa i izložbe o KGH, [S.l.], v. 56, n. 1, p. 329-340, feb. 2026.
Dostupno na: <https://izdanja.smeits.rs/index.php/kghk/article/view/8298>. Datum pristupa: 12 mar. 2026
Broj časopisa
Sekcija
nZEB gradnja za održivu budućnost – strateški pristup
Reference
[1] *** Intergovernmental Panel on Climate Change (IPCC), Climate Change 2022 – Impacts, Ad-aptation and Vulnerability, Cambridge University Press, 2023, https://doi.org/10.1017/ 9781009325844.
[2] Bavay M, Lehning M, Jonas T, Löwe H., Simulations of future snow cover and discharge in Alpine headwater catchments. Hydrol Process 2009; doi:10.1002/hyp.7195.
[3] Bony S, Colman R, Kattsov VM, Allan RP, Bretherton CS, Dufresne J-L, et al., How well do we understand and evaluate climate change feedback processes? J Climate 2006.
[4] Wana KKW, Lia DHW, Liub D, Lam JC., Future trends of building heating and cooling loads and energy consumption in different climates. Build Environ 2011.
[5] Anderson K, Bows A., Reframing the climate challenge in light of Post-2000 emissions trends. Philosophical Trans R Soc A 2008.
[6] Guan L., Preparation of future weather data to study the impact of climate change on buildings. Build Environ 2009.
[7] Ouedraogo BI, Levermore GJ, Parkinson JB., Future energy demand for public buildings in the context of climate change for Burkina Faso. Build Environ 2012.
[8] Wang X, Chen D, Ren Z., Assessment of climate change impact on residential building heating and cooling energy requirement in Australia. Build Environ 2010.
[9] Adelard L, Boyer H, Garde F, Gatina J-C., A detailed weather data generator for building simulations. Energ Build 2000.
[10] van Paassen AHC, Luo QX., Weather data generator to study climate change on buildings. Build Serv Eng Res Technol 2002.
[11] *** UKCIP02. Climate change scenarios for the United Kingdom. Available from: UKCIP.
[12] *** UK Climate Projections, http://ukclimateprojections.defra.gov.uk/; 2009
[13] D. Coakley, P. Raftery, P. Molloy, Calibration of whole building energy simulation models: detailed case study of a naturally ventilated building using hourly measured data. Presented at the 1st Building Simulation and Optimization Conference, Sep. 2012. Loughborough (UK).
[14] M. Royapoor, T. Roskilly, Building model calibration using energy and environmental data, Energy Build. 94 (May 2015) 109–120, https://doi.org/ 10.1016/j.enbuild.2015.02.050.
[15] A. Cacabelos, P. Eguía, J.L. Míguez, E. Granada, M.E. Arce, Calibrated simulation of a pub-lic library HVAC system with a ground-source heat pump and a radiant floor using TRNSYS and GenOpt, Energy Build. 108 (Dec. 2015) 114–126, https:// doi.org/10.1016/ j.enbuild.2015.09.006.
[16] P. Paliouras, N. Matzaflaras, R.H. Peuhkuri, J. Kolarik, Using measured indoor environ-ment parameters for calibration of building simulation model- A passive house case study, Ener-gy Proc. 78 (Nov. 2015) 1227–1232, https://doi.org/ 10.1016/j.egypro.2015.11.209.
[17] A. O’ Donovan, P.D. O’ Sullivan, M.D. Murphy, Predicting air temperatures in a naturally ventilated nearly zero energy building: calibration, validation, analysis and approaches, Appl. En-ergy 250 (Sep. 2019) 991–1010, https://doi.org/ 10.1016/j.apenergy.2019.04.082.
[18] F.M. Baba, H. Ge, R. Zmeureanu, L. Wang, Calibration of building model based on indoor temperature for overheating assessment using genetic algorithm: methodology, evaluation criteria, and case study, Build. Environ. 207 (Jan. 2022) 108518, https://doi.org/10.1016/j.buildenv.2021.108518.
[19] M. Hosseini, K. Javanroodi, V.M. Nik, High-resolution impact assessment of climate change on building energy performance considering extreme weather events and microclimate – investi-gating variations in indoor thermal comfort and M. Hostein et al. Building and Environment 263 (2024) 111874 15 degree-days, Sustain. Cities Soc. 78 (Mar. 2022) 103634, https://doi.org/10.1016/ j.scs.2021.103634.
[20] F.M. Baba, H. Ge, L. Leon Wang, R. Zmeureanu, Assessing and mitigating overheating risk in existing Canadian school buildings under extreme current and future climates, Energy Build. 279 (Jan. 2023) 112710, https://doi.org/10.1016/j. enbuild.2022.112710
[21] C.N. Nielsen, J. Kolarik, Utilization of climate files predicting future weather in dynamic build-ing performance simulation – a review, J. Phys.: Conf. Ser. 2069 (1) (Nov. 2021) 012070, https://doi.org/10.1088/1742-6596/2069/1/012070.
[22] A. Machard, C. Inard, J.-M. Alessandrini, C. Pel´e, J. Rib´eron, A methodology for assem-bling future weather files including heatwaves for building thermal simulations from the Europe-an coordinated regional downscaling experiment (EURO-CORDEX) climate data, Energies 13 (13) (Jan. 2020), https://doi.org/ 10.3390/en13133424. Art. no. 13
[23] A. Moazami, V.M. Nik, S. Carlucci, S. Geving, Impacts of future weather data typology on building energy performance – investigating long-term patterns of climate change and extreme weather conditions, Appl. Energy 238 (Mar. 2019) 696–720, https://doi.org/10.1016/j.apenergy.2019.01.085.
[24] Cowpertwait PSP, Kilsby C, O’Connell P., A space–time Neyman–Scott model of rainfall: empirical analysis of extremes. Water Resour Res 2002;38(8):1–14.
[25] Cowpertwait PSP., A Poisson-cluster model of rainfall: high order moments and extreme val-ues. Proc Roy Soc Lond Ser A 1998.
[26] G. Ouzeau, J.-M. Soubeyroux, M. Schneider, R. Vautard, S. Planton, Heat waves analysis over France in present and future climate: application of a new method on the EURO-CORDEX ensemble, Climate Services 4 (Dec. 2016) 1–12, https://doi. org/10.1016/j.cliser.2016.09.002.
[27] D. Amaripadath, R. Paolini, D.J. Sailor, S. Attia, Comparative assessment of night ventila-tion performance in a nearly zero-energy office building during heat waves in Brussels, J. Build. Eng. 78 (Nov. 2023) 107611, https://doi.org/10.1016/j. jobe.2023.107611.
[28] A. Machard, et al., Climate change influence on buildings dynamic thermal behavior during summer overheating periods: an in-depth sensitivity analysis, Energy Build. 284 (Apr. 2023) 112758, https://doi.org/10.1016/j. enbuild.2022.112758.
[29] J. Younes, et al., Enhancing sustainability and resilience of elderly dwellings: optimized refur-bishing parameters and air conditioning operation, Energy Build. 289 (Jun. 2023) 113065, https://doi.org/10.1016/j.enbuild.2023.113065.
[30] A. Toesca, D. David, K. Johannes, M. Lussault, Generation of weather data for the assess-ment of building performances under future heatwave conditions, Build. Environ. 242 (Aug. 2023) 110491, https://doi.org/10.1016/j. buildenv.2023.110491.
[31] S. Doutreloup, et al., Historical and future weather data for dynamic building simulations in Belgium using the regional climate model MAR: typical and extreme meteorological year and heatwaves, Earth Syst. Sci. Data 14 (7) (Jul. 2022) 3039–3051, https://doi.org/10.5194/essd-14-3039-2022.
[32] M. Herrera, et al., A review of current and future weather data for building simulation, Build. Serv. Eng. Res. Tecnol. 38 (5) (Sep. 2017) 602–627, https://doi. org/10.1177/0143624417705937.
[33] *** 1. Intergovernmental Panel on Climate Change (IPCC). Framing and Context. In: Global Warming of 1.5°C: IPCC Special Report on Impacts of Global Warming of 1.5°C above Pre-Industrial Levels in Context of Strengthening Response to Climate Change, Sustainable Devel-opment, and Efforts to Eradicate Poverty. Cambridge University Press; 2022:49-92.
[2] Bavay M, Lehning M, Jonas T, Löwe H., Simulations of future snow cover and discharge in Alpine headwater catchments. Hydrol Process 2009; doi:10.1002/hyp.7195.
[3] Bony S, Colman R, Kattsov VM, Allan RP, Bretherton CS, Dufresne J-L, et al., How well do we understand and evaluate climate change feedback processes? J Climate 2006.
[4] Wana KKW, Lia DHW, Liub D, Lam JC., Future trends of building heating and cooling loads and energy consumption in different climates. Build Environ 2011.
[5] Anderson K, Bows A., Reframing the climate challenge in light of Post-2000 emissions trends. Philosophical Trans R Soc A 2008.
[6] Guan L., Preparation of future weather data to study the impact of climate change on buildings. Build Environ 2009.
[7] Ouedraogo BI, Levermore GJ, Parkinson JB., Future energy demand for public buildings in the context of climate change for Burkina Faso. Build Environ 2012.
[8] Wang X, Chen D, Ren Z., Assessment of climate change impact on residential building heating and cooling energy requirement in Australia. Build Environ 2010.
[9] Adelard L, Boyer H, Garde F, Gatina J-C., A detailed weather data generator for building simulations. Energ Build 2000.
[10] van Paassen AHC, Luo QX., Weather data generator to study climate change on buildings. Build Serv Eng Res Technol 2002.
[11] *** UKCIP02. Climate change scenarios for the United Kingdom. Available from: UKCIP.
[12] *** UK Climate Projections, http://ukclimateprojections.defra.gov.uk/; 2009
[13] D. Coakley, P. Raftery, P. Molloy, Calibration of whole building energy simulation models: detailed case study of a naturally ventilated building using hourly measured data. Presented at the 1st Building Simulation and Optimization Conference, Sep. 2012. Loughborough (UK).
[14] M. Royapoor, T. Roskilly, Building model calibration using energy and environmental data, Energy Build. 94 (May 2015) 109–120, https://doi.org/ 10.1016/j.enbuild.2015.02.050.
[15] A. Cacabelos, P. Eguía, J.L. Míguez, E. Granada, M.E. Arce, Calibrated simulation of a pub-lic library HVAC system with a ground-source heat pump and a radiant floor using TRNSYS and GenOpt, Energy Build. 108 (Dec. 2015) 114–126, https:// doi.org/10.1016/ j.enbuild.2015.09.006.
[16] P. Paliouras, N. Matzaflaras, R.H. Peuhkuri, J. Kolarik, Using measured indoor environ-ment parameters for calibration of building simulation model- A passive house case study, Ener-gy Proc. 78 (Nov. 2015) 1227–1232, https://doi.org/ 10.1016/j.egypro.2015.11.209.
[17] A. O’ Donovan, P.D. O’ Sullivan, M.D. Murphy, Predicting air temperatures in a naturally ventilated nearly zero energy building: calibration, validation, analysis and approaches, Appl. En-ergy 250 (Sep. 2019) 991–1010, https://doi.org/ 10.1016/j.apenergy.2019.04.082.
[18] F.M. Baba, H. Ge, R. Zmeureanu, L. Wang, Calibration of building model based on indoor temperature for overheating assessment using genetic algorithm: methodology, evaluation criteria, and case study, Build. Environ. 207 (Jan. 2022) 108518, https://doi.org/10.1016/j.buildenv.2021.108518.
[19] M. Hosseini, K. Javanroodi, V.M. Nik, High-resolution impact assessment of climate change on building energy performance considering extreme weather events and microclimate – investi-gating variations in indoor thermal comfort and M. Hostein et al. Building and Environment 263 (2024) 111874 15 degree-days, Sustain. Cities Soc. 78 (Mar. 2022) 103634, https://doi.org/10.1016/ j.scs.2021.103634.
[20] F.M. Baba, H. Ge, L. Leon Wang, R. Zmeureanu, Assessing and mitigating overheating risk in existing Canadian school buildings under extreme current and future climates, Energy Build. 279 (Jan. 2023) 112710, https://doi.org/10.1016/j. enbuild.2022.112710
[21] C.N. Nielsen, J. Kolarik, Utilization of climate files predicting future weather in dynamic build-ing performance simulation – a review, J. Phys.: Conf. Ser. 2069 (1) (Nov. 2021) 012070, https://doi.org/10.1088/1742-6596/2069/1/012070.
[22] A. Machard, C. Inard, J.-M. Alessandrini, C. Pel´e, J. Rib´eron, A methodology for assem-bling future weather files including heatwaves for building thermal simulations from the Europe-an coordinated regional downscaling experiment (EURO-CORDEX) climate data, Energies 13 (13) (Jan. 2020), https://doi.org/ 10.3390/en13133424. Art. no. 13
[23] A. Moazami, V.M. Nik, S. Carlucci, S. Geving, Impacts of future weather data typology on building energy performance – investigating long-term patterns of climate change and extreme weather conditions, Appl. Energy 238 (Mar. 2019) 696–720, https://doi.org/10.1016/j.apenergy.2019.01.085.
[24] Cowpertwait PSP, Kilsby C, O’Connell P., A space–time Neyman–Scott model of rainfall: empirical analysis of extremes. Water Resour Res 2002;38(8):1–14.
[25] Cowpertwait PSP., A Poisson-cluster model of rainfall: high order moments and extreme val-ues. Proc Roy Soc Lond Ser A 1998.
[26] G. Ouzeau, J.-M. Soubeyroux, M. Schneider, R. Vautard, S. Planton, Heat waves analysis over France in present and future climate: application of a new method on the EURO-CORDEX ensemble, Climate Services 4 (Dec. 2016) 1–12, https://doi. org/10.1016/j.cliser.2016.09.002.
[27] D. Amaripadath, R. Paolini, D.J. Sailor, S. Attia, Comparative assessment of night ventila-tion performance in a nearly zero-energy office building during heat waves in Brussels, J. Build. Eng. 78 (Nov. 2023) 107611, https://doi.org/10.1016/j. jobe.2023.107611.
[28] A. Machard, et al., Climate change influence on buildings dynamic thermal behavior during summer overheating periods: an in-depth sensitivity analysis, Energy Build. 284 (Apr. 2023) 112758, https://doi.org/10.1016/j. enbuild.2022.112758.
[29] J. Younes, et al., Enhancing sustainability and resilience of elderly dwellings: optimized refur-bishing parameters and air conditioning operation, Energy Build. 289 (Jun. 2023) 113065, https://doi.org/10.1016/j.enbuild.2023.113065.
[30] A. Toesca, D. David, K. Johannes, M. Lussault, Generation of weather data for the assess-ment of building performances under future heatwave conditions, Build. Environ. 242 (Aug. 2023) 110491, https://doi.org/10.1016/j. buildenv.2023.110491.
[31] S. Doutreloup, et al., Historical and future weather data for dynamic building simulations in Belgium using the regional climate model MAR: typical and extreme meteorological year and heatwaves, Earth Syst. Sci. Data 14 (7) (Jul. 2022) 3039–3051, https://doi.org/10.5194/essd-14-3039-2022.
[32] M. Herrera, et al., A review of current and future weather data for building simulation, Build. Serv. Eng. Res. Tecnol. 38 (5) (Sep. 2017) 602–627, https://doi. org/10.1177/0143624417705937.
[33] *** 1. Intergovernmental Panel on Climate Change (IPCC). Framing and Context. In: Global Warming of 1.5°C: IPCC Special Report on Impacts of Global Warming of 1.5°C above Pre-Industrial Levels in Context of Strengthening Response to Climate Change, Sustainable Devel-opment, and Efforts to Eradicate Poverty. Cambridge University Press; 2022:49-92.