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Analysis of uncertainty indices used for building envelope calibration

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  • Ramos Ruiz, Germán
  • Fernández Bandera, Carlos

Abstract

Nowadays there is a growing concern about climate change and the global warming effect produced by the concentration of greenhouse gases (GHG). At the Paris climate conference (COP21), 195 countries adopted a global climate agreement, limiting global warming to well below 2°C. Buildings are large producers of GHG and therefore international standards such as ISO 50001 focus on improving their energy performance, including energy efficiency, use and consumption. To achieve this goal it is important to have a detailed knowledge of the thermal behaviour of buildings. The International Performance Measurement and Verification Protocol (IPMVP), proposes a calibrated simulation model (Option D) to gather this knowledge and to determine the savings associated with Energy Conservation Measures (ECMs).

Suggested Citation

  • Ramos Ruiz, Germán & Fernández Bandera, Carlos, 2017. "Analysis of uncertainty indices used for building envelope calibration," Applied Energy, Elsevier, vol. 185(P1), pages 82-94.
    • Handle: RePEc:eee:appene:v:185:y:2017:i:p1:p:82-94
    DOI: 10.1016/j.apenergy.2016.10.054
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    6. Ramos Ruiz, Germán & Fernández Bandera, Carlos & Gómez-Acebo Temes, Tomás & Sánchez-Ostiz Gutierrez, Ana, 2016. "Genetic algorithm for building envelope calibration," Applied Energy, Elsevier, vol. 168(C), pages 691-705.
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    Cited by:

    1. Wang, Fei-Long & He, Ya-Ling & Tang, Song-Zhen & Kulacki, Francis A. & Tao, Yu-Bing, 2019. "Multi-objective optimization of a dual-layer granular filter for hot gas clean-up by using genetic algorithm," Applied Energy, Elsevier, vol. 248(C), pages 463-474.
    2. José Sánchez Ramos & MCarmen Guerrero Delgado & Servando Álvarez Domínguez & José Luis Molina Félix & Francisco José Sánchez de la Flor & José Antonio Tenorio Ríos, 2019. "Systematic Simplified Simulation Methodology for Deep Energy Retrofitting Towards Nze Targets Using Life Cycle Energy Assessment," Energies, MDPI, vol. 12(16), pages 1-27, August.
    3. Chen, Hanfei & Lin, ChihChieh & Longtin, Jon P., 2019. "Dynamic modeling and parameter optimization of a free-piston Vuilleumier heat pump with dwell-based motion," Applied Energy, Elsevier, vol. 242(C), pages 741-751.
    4. Wang, Kun & He, Ya-Ling & Xue, Xiao-Dai & Du, Bao-Cun, 2017. "Multi-objective optimization of the aiming strategy for the solar power tower with a cavity receiver by using the non-dominated sorting genetic algorithm," Applied Energy, Elsevier, vol. 205(C), pages 399-416.
    5. Lee, Junghun & Kim, Seohoon & Kim, Jonghun & Song, Doosam & Jeong, Hakgeun, 2018. "Thermal performance evaluation of low-income buildings based on indoor temperature performance," Applied Energy, Elsevier, vol. 221(C), pages 425-436.
    6. Vicente Gutiérrez González & Lissette Álvarez Colmenares & Jesús Fernando López Fidalgo & Germán Ramos Ruiz & Carlos Fernández Bandera, 2019. "Uncertainy’s Indices Assessment for Calibrated Energy Models," Energies, MDPI, vol. 12(11), pages 1-18, May.
    7. Juricic, Sarah & Goffart, Jeanne & Rouchier, Simon & Foucquier, Aurélie & Cellier, Nicolas & Fraisse, Gilles, 2021. "Influence of natural weather variability on the thermal characterisation of a building envelope," Applied Energy, Elsevier, vol. 288(C).
    8. Eva Lucas Segarra & Germán Ramos Ruiz & Vicente Gutiérrez González & Antonis Peppas & Carlos Fernández Bandera, 2020. "Impact Assessment for Building Energy Models Using Observed vs. Third-Party Weather Data Sets," Sustainability, MDPI, vol. 12(17), pages 1-27, August.
    9. Carlos Fernández Bandera & Germán Ramos Ruiz, 2017. "Towards a New Generation of Building Envelope Calibration," Energies, MDPI, vol. 10(12), pages 1-19, December.
    10. Vicente Gutiérrez González & Germán Ramos Ruiz & Carlos Fernández Bandera, 2021. "Impact of Actual Weather Datasets for Calibrating White-Box Building Energy Models Base on Monitored Data," Energies, MDPI, vol. 14(4), pages 1-16, February.
    11. Younghoon Kwak & Jeonga Kang & Sun-Hye Mun & Young-Sun Jeong & Jung-Ho Huh, 2020. "Development and Application of a Flexible Modeling Approach to Reference Buildings for Energy Analysis," Energies, MDPI, vol. 13(21), pages 1-22, November.
    12. Wang, Kun & Li, Ming-Jia & Guo, Jia-Qi & Li, Peiwen & Liu, Zhan-Bin, 2018. "A systematic comparison of different S-CO2 Brayton cycle layouts based on multi-objective optimization for applications in solar power tower plants," Applied Energy, Elsevier, vol. 212(C), pages 109-121.
    13. Carlos Fernández Bandera & Ana Fei Muñoz Mardones & Hu Du & Juan Echevarría Trueba & Germán Ramos Ruiz, 2018. "Exergy As a Measure of Sustainable Retrofitting of Buildings," Energies, MDPI, vol. 11(11), pages 1-19, November.
    14. Germán Ramos Ruiz & Eva Lucas Segarra & Carlos Fernández Bandera, 2018. "Model Predictive Control Optimization via Genetic Algorithm Using a Detailed Building Energy Model," Energies, MDPI, vol. 12(1), pages 1-18, December.
    15. Germán Ramos Ruiz & Carlos Fernández Bandera, 2017. "Validation of Calibrated Energy Models: Common Errors," Energies, MDPI, vol. 10(10), pages 1-19, October.
    16. Eva Lucas Segarra & Hu Du & Germán Ramos Ruiz & Carlos Fernández Bandera, 2019. "Methodology for the Quantification of the Impact of Weather Forecasts in Predictive Simulation Models," Energies, MDPI, vol. 12(7), pages 1-16, April.
    17. Carlos Fernández Bandera & Jose Pachano & Jaume Salom & Antonis Peppas & Germán Ramos Ruiz, 2020. "Photovoltaic Plant Optimization to Leverage Electric Self Consumption by Harnessing Building Thermal Mass," Sustainability, MDPI, vol. 12(2), pages 1-20, January.

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