Application of a Monte Carlo model to predict space heating energy use of Belgrades housing stock
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2015
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Detailed domestic stock energy models can be used to help formulate optimum energy reduction strategies. However, there will always be considerable uncertainty related to their predictions due to the complexity of the housing stock and the many assumptions required to implement the models. This paper presents a simple Monte Carlo (MC) model that can be easily extended and/or transformed in relation to data available for investigating and quantifying uncertainties in both the housing stock models predictions and scenario assumptions. While 90% of the MC model predictions fell within a range which is +/- 19% the mean value, 50% of them were within +/- 8% of the mean. The findings suggest that the uncertainties associated with the model predictions and scenario assumptions need to be acknowledged fully and - where possible - quantified as even fairly small variability in the influential variables may result in rather large uncertainty in the aggregated models prediction.
Ključne reči:
Monte Carlo method / uncertainty analysis / explorative scenarios / domestic space heating energy use / domestic energy modelsIzvor:
Journal of Building Performance Simulation, 2015, 8, 6, 375-390Izdavač:
- Taylor & Francis
DOI: 10.1080/19401493.2014.961031
ISSN: 1940-1493; 1940-1507
WoS: 000365657200001
Scopus: 2-s2.0-84948581805
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Institucija/grupa
VinčaTY - JOUR AU - Kavgic, Miroslava AU - Summerfield, Alex AU - Mumovic, Dejan AU - Stevanović, Žarko M. PY - 2015 UR - https://vinar.vin.bg.ac.rs/handle/123456789/834 AB - Detailed domestic stock energy models can be used to help formulate optimum energy reduction strategies. However, there will always be considerable uncertainty related to their predictions due to the complexity of the housing stock and the many assumptions required to implement the models. This paper presents a simple Monte Carlo (MC) model that can be easily extended and/or transformed in relation to data available for investigating and quantifying uncertainties in both the housing stock models predictions and scenario assumptions. While 90% of the MC model predictions fell within a range which is +/- 19% the mean value, 50% of them were within +/- 8% of the mean. The findings suggest that the uncertainties associated with the model predictions and scenario assumptions need to be acknowledged fully and - where possible - quantified as even fairly small variability in the influential variables may result in rather large uncertainty in the aggregated models prediction. PB - Taylor & Francis T2 - Journal of Building Performance Simulation T1 - Application of a Monte Carlo model to predict space heating energy use of Belgrades housing stock VL - 8 IS - 6 SP - 375 EP - 390 DO - 10.1080/19401493.2014.961031 ER -
@article{ author = "Kavgic, Miroslava and Summerfield, Alex and Mumovic, Dejan and Stevanović, Žarko M.", year = "2015", abstract = "Detailed domestic stock energy models can be used to help formulate optimum energy reduction strategies. However, there will always be considerable uncertainty related to their predictions due to the complexity of the housing stock and the many assumptions required to implement the models. This paper presents a simple Monte Carlo (MC) model that can be easily extended and/or transformed in relation to data available for investigating and quantifying uncertainties in both the housing stock models predictions and scenario assumptions. While 90% of the MC model predictions fell within a range which is +/- 19% the mean value, 50% of them were within +/- 8% of the mean. The findings suggest that the uncertainties associated with the model predictions and scenario assumptions need to be acknowledged fully and - where possible - quantified as even fairly small variability in the influential variables may result in rather large uncertainty in the aggregated models prediction.", publisher = "Taylor & Francis", journal = "Journal of Building Performance Simulation", title = "Application of a Monte Carlo model to predict space heating energy use of Belgrades housing stock", volume = "8", number = "6", pages = "375-390", doi = "10.1080/19401493.2014.961031" }
Kavgic, M., Summerfield, A., Mumovic, D.,& Stevanović, Ž. M.. (2015). Application of a Monte Carlo model to predict space heating energy use of Belgrades housing stock. in Journal of Building Performance Simulation Taylor & Francis., 8(6), 375-390. https://doi.org/10.1080/19401493.2014.961031
Kavgic M, Summerfield A, Mumovic D, Stevanović ŽM. Application of a Monte Carlo model to predict space heating energy use of Belgrades housing stock. in Journal of Building Performance Simulation. 2015;8(6):375-390. doi:10.1080/19401493.2014.961031 .
Kavgic, Miroslava, Summerfield, Alex, Mumovic, Dejan, Stevanović, Žarko M., "Application of a Monte Carlo model to predict space heating energy use of Belgrades housing stock" in Journal of Building Performance Simulation, 8, no. 6 (2015):375-390, https://doi.org/10.1080/19401493.2014.961031 . .