IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i6p807-d101466.html
   My bibliography  Save this article

Energy Modelling and Automated Calibrations of Ancient Building Simulations: A Case Study of a School in the Northwest of Spain

Author

Listed:
  • Ana Ogando

    (Department of Mechanical Engineering, Heat Engines and Fluid Mechanics, School of Industrial Engineering, University of Vigo, Vigo 36310, Spain)

  • Natalia Cid

    (Department of Mechanical Engineering, Heat Engines and Fluid Mechanics, School of Industrial Engineering, University of Vigo, Vigo 36310, Spain)

  • Marta Fernández

    (Department of Mechanical Engineering, Heat Engines and Fluid Mechanics, School of Industrial Engineering, University of Vigo, Vigo 36310, Spain)

Abstract

In the present paper, the energy performance of buildings forming a school centre in the northwest of Spain was analyzed using a transient simulation of the energy model of the school, which was developed with TRNSYS, a software of proven reliability in the field of thermal simulations. A deterministic calibration approach was applied to the initial building model to adjust the predictions to the actual performance of the school, data acquired during the temperature measurement campaign. The buildings under study were in deteriorated conditions due to poor maintenance over the years, presenting a big challenge for modelling and simulating it in a reliable way. The results showed that the proposed methodology is successful for obtaining calibrated thermal models of these types of damaged buildings, as the metrics employed to verify the final error showed a reduced normalized mean bias error (NMBE) of 2.73%. It was verified that a decrease of approximately 60% in NMBE and 17% in the coefficient of variation of the root mean square error (CV(RMSE)) was achieved due to the calibration process. Subsequent steps were performed with the aid of new software, which was developed under a European project that enabled the automated calibration of the simulations.

Suggested Citation

  • Ana Ogando & Natalia Cid & Marta Fernández, 2017. "Energy Modelling and Automated Calibrations of Ancient Building Simulations: A Case Study of a School in the Northwest of Spain," Energies, MDPI, vol. 10(6), pages 1-17, June.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:6:p:807-:d:101466
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/6/807/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/10/6/807/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ciulla, Giuseppina & Lo Brano, Valerio & D’Amico, Antonino, 2016. "Modelling relationship among energy demand, climate and office building features: A cluster analysis at European level," Applied Energy, Elsevier, vol. 183(C), pages 1021-1034.
    2. Anna Laura Pisello & Michael Bobker & Franco Cotana, 2012. "A Building Energy Efficiency Optimization Method by Evaluating the Effective Thermal Zones Occupancy," Energies, MDPI, vol. 5(12), pages 1-22, December.
    3. Enrico Fabrizio & Valentina Monetti, 2015. "Methodologies and Advancements in the Calibration of Building Energy Models," Energies, MDPI, vol. 8(4), pages 1-27, March.
    4. Young Tae Chae & Young M. Lee & David Longinott, 2016. "Assessment of Retrofitting Measures for a Large Historic Research Facility Using a Building Energy Simulation Model," Energies, MDPI, vol. 9(6), pages 1-18, June.
    5. Guillermo Rey & Carlos Ulloa & José Luís Míguez & Antón Cacabelos, 2016. "Suitability Assessment of an ICE-Based Micro-CCHP Unit in Different Spanish Climatic Zones: Application of an Experimental Model in Transient Simulation," Energies, MDPI, vol. 9(11), pages 1-13, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Joanna Ferdyn-Grygierek & Dorota Bartosz & Aleksandra Specjał & Krzysztof Grygierek, 2018. "Analysis of Accuracy Determination of the Seasonal Heat Demand in Buildings Based on Short Measurement Periods," Energies, MDPI, vol. 11(10), pages 1-19, October.
    2. Ceballos-Fuentealba, Irlanda & Álvarez-Miranda, Eduardo & Torres-Fuchslocher, Carlos & del Campo-Hitschfeld, María Luisa & Díaz-Guerrero, John, 2019. "A simulation and optimisation methodology for choosing energy efficiency measures in non-residential buildings," Applied Energy, Elsevier, vol. 256(C).
    3. Santos-Herrero, J.M. & Lopez-Guede, J.M. & Flores-Abascal, I., 2021. "Modeling, simulation and control tools for nZEB: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 142(C).
    4. Michael D. Murphy & Paul D. O’Sullivan & Guilherme Carrilho da Graça & Adam O’Donovan, 2021. "Development, Calibration and Validation of an Internal Air Temperature Model for a Naturally Ventilated Nearly Zero Energy Building: Comparison of Model Types and Calibration Methods," Energies, MDPI, vol. 14(4), pages 1-24, February.
    5. Akkurt, G.G. & Aste, N. & Borderon, J. & Buda, A. & Calzolari, M. & Chung, D. & Costanzo, V. & Del Pero, C. & Evola, G. & Huerto-Cardenas, H.E. & Leonforte, F. & Lo Faro, A. & Lucchi, E. & Marletta, L, 2020. "Dynamic thermal and hygrometric simulation of historical buildings: Critical factors and possible solutions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
    6. Carolina Aparicio-Fernández & José-Luis Vivancos & Paula Cosar-Jorda & Richard A. Buswell, 2019. "Energy Modelling and Calibration of Building Simulations: A Case Study of a Domestic Building with Natural Ventilation," Energies, MDPI, vol. 12(17), pages 1-13, August.
    7. O' Donovan, Adam & O' Sullivan, Paul D. & Murphy, Michael D., 2019. "Predicting air temperatures in a naturally ventilated nearly zero energy building: Calibration, validation, analysis and approaches," Applied Energy, Elsevier, vol. 250(C), pages 991-1010.
    8. Roberto Zanetti Freire & Gerson Henrique dos Santos & Leandro dos Santos Coelho, 2017. "Hygrothermal Dynamic and Mould Growth Risk Predictions for Concrete Tiles by Using Least Squares Support Vector Machines," Energies, MDPI, vol. 10(8), pages 1-16, July.
    9. Germán Ramos Ruiz & Carlos Fernández Bandera, 2017. "Validation of Calibrated Energy Models: Common Errors," Energies, MDPI, vol. 10(10), pages 1-19, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Massimiliano Manfren & Benedetto Nastasi, 2020. "Parametric Performance Analysis and Energy Model Calibration Workflow Integration—A Scalable Approach for Buildings," Energies, MDPI, vol. 13(3), pages 1-14, February.
    2. Arkar, C. & Žižak, T. & Domjan, S. & Medved, S., 2020. "Dynamic parametric models for the holistic evaluation of semi-transparent photovoltaic/thermal façade with latent storage inserts," Applied Energy, Elsevier, vol. 280(C).
    3. Villa-Arrieta, Manuel & Sumper, Andreas, 2018. "A model for an economic evaluation of energy systems using TRNSYS," Applied Energy, Elsevier, vol. 215(C), pages 765-777.
    4. Solène Goy & François Maréchal & Donal Finn, 2020. "Data for Urban Scale Building Energy Modelling: Assessing Impacts and Overcoming Availability Challenges," Energies, MDPI, vol. 13(16), pages 1-23, August.
    5. Nutkiewicz, Alex & Yang, Zheng & Jain, Rishee K., 2018. "Data-driven Urban Energy Simulation (DUE-S): A framework for integrating engineering simulation and machine learning methods in a multi-scale urban energy modeling workflow," Applied Energy, Elsevier, vol. 225(C), pages 1176-1189.
    6. Ahmed, Omar & Sezer, Nurettin & Ouf, Mohamed & Wang, Liangzhu (Leon) & Hassan, Ibrahim Galal, 2023. "State-of-the-art review of occupant behavior modeling and implementation in building performance simulation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).
    7. D'Amico, A. & Ciulla, G. & Panno, D. & Ferrari, S., 2019. "Building energy demand assessment through heating degree days: The importance of a climatic dataset," Applied Energy, Elsevier, vol. 242(C), pages 1285-1306.
    8. Mehdi Taebnia & Sander Toomla & Lauri Leppä & Jarek Kurnitski, 2019. "Air Distribution and Air Handling Unit Configuration Effects on Energy Performance in an Air-Heated Ice Rink Arena," Energies, MDPI, vol. 12(4), pages 1-21, February.
    9. Reynolds, Jonathan & Rezgui, Yacine & Kwan, Alan & Piriou, Solène, 2018. "A zone-level, building energy optimisation combining an artificial neural network, a genetic algorithm, and model predictive control," Energy, Elsevier, vol. 151(C), pages 729-739.
    10. Francesco Asdrubali & Cinzia Buratti & Franco Cotana & Giorgio Baldinelli & Michele Goretti & Elisa Moretti & Catia Baldassarri & Elisa Belloni & Francesco Bianchi & Antonella Rotili & Marco Vergoni &, 2013. "Evaluation of Green Buildings’ Overall Performance through in Situ Monitoring and Simulations," Energies, MDPI, vol. 6(12), pages 1-23, December.
    11. Yuan, Jun & Nian, Victor & Su, Bin & Meng, Qun, 2017. "A simultaneous calibration and parameter ranking method for building energy models," Applied Energy, Elsevier, vol. 206(C), pages 657-666.
    12. Suzana Domjan & Sašo Medved & Boštjan Černe & Ciril Arkar, 2019. "Fast Modelling of nZEB Metrics of Office Buildings Built with Advanced Glass and BIPV Facade Structures," Energies, MDPI, vol. 12(16), pages 1-18, August.
    13. Guozheng Li & Rui Wang & Tao Zhang & Mengjun Ming, 2018. "Multi-Objective Optimal Design of Renewable Energy Integrated CCHP System Using PICEA-g," Energies, MDPI, vol. 11(4), pages 1-26, March.
    14. Cristina Brunelli & Francesco Castellani & Alberto Garinei & Lorenzo Biondi & Marcello Marconi, 2016. "A Procedure to Perform Multi-Objective Optimization for Sustainable Design of Buildings," Energies, MDPI, vol. 9(11), pages 1-15, November.
    15. Dario Cottafava & Giulia Sonetti & Paolo Gambino & Andrea Tartaglino, 2018. "Explorative Multidimensional Analysis for Energy Efficiency: DataViz versus Clustering Algorithms," Energies, MDPI, vol. 11(5), pages 1-18, May.
    16. Fabrizio M. Amoruso & Udo Dietrich & Thorsten Schuetze, 2019. "Indoor Thermal Comfort Improvement through the Integrated BIM-Parametric Workflow-Based Sustainable Renovation of an Exemplary Apartment in Seoul, Korea," Sustainability, MDPI, vol. 11(14), pages 1-31, July.
    17. Pedro Paulo Fernandes da Silva & Alberto Hernandez Neto & Ildo Luis Sauer, 2021. "Evaluation of Model Calibration Method for Simulation Performance of a Public Hospital in Brazil," Energies, MDPI, vol. 14(13), pages 1-20, June.
    18. Attia, Shady & Canonge, Théophile & Popineau, Mathieu & Cuchet, Mathilde, 2022. "Developing a benchmark model for renovated, nearly zero-energy, terraced dwellings," Applied Energy, Elsevier, vol. 306(PB).
    19. Rafael Sánchez-Durán & Joaquín Luque & Julio Barbancho, 2019. "Long-Term Demand Forecasting in a Scenario of Energy Transition," Energies, MDPI, vol. 12(16), pages 1-23, August.
    20. Byung-Ki Jeon & Eui-Jong Kim, 2021. "LSTM-Based Model Predictive Control for Optimal Temperature Set-Point Planning," Sustainability, MDPI, vol. 13(2), pages 1-14, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:10:y:2017:i:6:p:807-:d:101466. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.