IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i23p8904-d983671.html
   My bibliography  Save this article

Impact on Thermal Energy Needs Caused by the Use of Different Solar Irradiance Decomposition and Transposition Models: Application of EN ISO 52016-1 and EN ISO 52010-1 Standards for Five European Cities

Author

Listed:
  • Serena Summa

    (Industrial Engineering and Mathematical Sciences Department, Università Politecnica delle Marche, Via Brecce Bianche 1, 60131 Ancona, Italy)

  • Giada Remia

    (Industrial Engineering and Mathematical Sciences Department, Università Politecnica delle Marche, Via Brecce Bianche 1, 60131 Ancona, Italy)

  • Ambra Sebastianelli

    (Industrial Engineering and Mathematical Sciences Department, Università Politecnica delle Marche, Via Brecce Bianche 1, 60131 Ancona, Italy)

  • Gianluca Coccia

    (Industrial Engineering and Mathematical Sciences Department, Università Politecnica delle Marche, Via Brecce Bianche 1, 60131 Ancona, Italy)

  • Costanzo Di Perna

    (Industrial Engineering and Mathematical Sciences Department, Università Politecnica delle Marche, Via Brecce Bianche 1, 60131 Ancona, Italy)

Abstract

To solve the series of heat balances that EN ISO 52016-1 uses to simulate the dynamic hourly energy requirements of a building, detailed climatic data are required as input. Differently from air temperatures, relative humidity and wind speed, which are easily measurable and available in databases, the direct and diffuse solar irradiances incident on the different inclined and oriented surfaces, which are fundamental for the evaluation of solar gains, must be estimated using one of the many regression models available in the literature. Therefore, in this work, the energy needs of buildings were evaluated with the simplified hourly dynamic method of EN ISO 52016-1 by varying the solar irradiance sets on inclined and oriented surfaces obtained from EN ISO 52010-1 and three other pairs of solar irradiance separation and transposition models. Five European locations and two different window solar transmission coefficients (g gl ) were analysed. The results showed that on average, for the heating period and for both g gl , the use of the different methods causes an average error on the calculation of the annual demand of less or slightly more than 5%; while for the cooling period, the average error on the calculation of the annual demand is 16.4% for the case study with g gl = 0.28 and 25.1% for the case study with g gl = 0.63. On the other hand, analysing the root-mean-square-error of the hourly data, using the model contained in TRNSYS as a benchmark, for most of the cases, when varying window orientations, cities and g gl , the model that diverges furthest from the others is that contained in EN ISO 52010-1.

Suggested Citation

  • Serena Summa & Giada Remia & Ambra Sebastianelli & Gianluca Coccia & Costanzo Di Perna, 2022. "Impact on Thermal Energy Needs Caused by the Use of Different Solar Irradiance Decomposition and Transposition Models: Application of EN ISO 52016-1 and EN ISO 52010-1 Standards for Five European Citi," Energies, MDPI, vol. 15(23), pages 1-18, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:23:p:8904-:d:983671
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/23/8904/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/23/8904/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ilaria Ballarini & Andrea Costantino & Enrico Fabrizio & Vincenzo Corrado, 2020. "A Methodology to Investigate the Deviations between Simple and Detailed Dynamic Methods for the Building Energy Performance Assessment," Energies, MDPI, vol. 13(23), pages 1-19, November.
    2. Zakula, Tea & Badun, Nikola & Ferdelji, Nenad & Ugrina, Ivo, 2021. "Framework for the ISO 52016 standard accuracy prediction based on the in-depth sensitivity analysis," Applied Energy, Elsevier, vol. 298(C).
    3. Li, Honglian & Yang, Yi & Lv, Kailin & Liu, Jing & Yang, Liu, 2020. "Compare several methods of select typical meteorological year for building energy simulation in China," Energy, Elsevier, vol. 209(C).
    4. Radhi, Hassan, 2009. "A comparison of the accuracy of building energy analysis in Bahrain using data from different weather periods," Renewable Energy, Elsevier, vol. 34(3), pages 869-875.
    5. Piotr Michalak, 2021. "Modelling of Solar Irradiance Incident on Building Envelopes in Polish Climatic Conditions: The Impact on Energy Performance Indicators of Residential Buildings," Energies, MDPI, vol. 14(14), pages 1-27, July.
    6. Li, Danny H.W. & Cheung, Gary H.W., 2005. "Study of models for predicting the diffuse irradiance on inclined surfaces," Applied Energy, Elsevier, vol. 81(2), pages 170-186, June.
    7. Boland, John & Ridley, Barbara & Brown, Bruce, 2008. "Models of diffuse solar radiation," Renewable Energy, Elsevier, vol. 33(4), pages 575-584.
    Full references (including those not matched with items on IDEAS)

    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. Piotr Michalak, 2022. "Impact of Air Density Variation on a Simulated Earth-to-Air Heat Exchanger’s Performance," Energies, MDPI, vol. 15(9), pages 1-24, April.
    2. Vincenzo Costanzo & Gianpiero Evola & Marco Infantone & Luigi Marletta, 2020. "Updated Typical Weather Years for the Energy Simulation of Buildings in Mediterranean Climate. A Case Study for Sicily," Energies, MDPI, vol. 13(16), pages 1-24, August.
    3. Giovanna De Luca & Franz Bianco Mauthe Degerfeld & Ilaria Ballarini & Vincenzo Corrado, 2021. "Accuracy of Simplified Modelling Assumptions on External and Internal Driving Forces in the Building Energy Performance Simulation," Energies, MDPI, vol. 14(20), pages 1-22, October.
    4. Pulkkinen, Jari & Louis, Jean-Nicolas & Debusschere, Vincent & Pongrácz, Eva, 2024. "Near-, medium- and long-term impacts of climate change on the thermal energy consumption of buildings in Finland under RCP climate scenarios," Energy, Elsevier, vol. 302(C).
    5. Torres, J.L. & García, A. & de Blas, M. & Gracia, A. & Illanes, R., 2010. "A study of zenith radiance in Pamplona under different sky conditions," Renewable Energy, Elsevier, vol. 35(4), pages 830-838.
    6. El-Sebaii, A.A. & Al-Hazmi, F.S. & Al-Ghamdi, A.A. & Yaghmour, S.J., 2010. "Global, direct and diffuse solar radiation on horizontal and tilted surfaces in Jeddah, Saudi Arabia," Applied Energy, Elsevier, vol. 87(2), pages 568-576, February.
    7. Cui, Ying & Yan, Da & Hong, Tianzhen & Xiao, Chan & Luo, Xuan & Zhang, Qi, 2017. "Comparison of typical year and multiyear building simulations using a 55-year actual weather data set from China," Applied Energy, Elsevier, vol. 195(C), pages 890-904.
    8. Yau, Y.H. & Pean, H.L., 2011. "The climate change impact on air conditioner system and reliability in Malaysia—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4939-4949.
    9. Jamil, Basharat & Akhtar, Naiem, 2017. "Comparison of empirical models to estimate monthly mean diffuse solar radiation from measured data: Case study for humid-subtropical climatic region of India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1326-1342.
    10. Icaro Figueiredo Vilasboas & Julio Augusto Mendes da Silva & Osvaldo José Venturini, 2023. "On the Summarization of Meteorological Data for Solar Thermal Power Generation Forecast," Energies, MDPI, vol. 16(7), pages 1-10, April.
    11. 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.
    12. Li, Danny H.W. & Lou, Siwei, 2018. "Review of solar irradiance and daylight illuminance modeling and sky classification," Renewable Energy, Elsevier, vol. 126(C), pages 445-453.
    13. Feng, Lan & Lin, Aiwen & Wang, Lunche & Qin, Wenmin & Gong, Wei, 2018. "Evaluation of sunshine-based models for predicting diffuse solar radiation in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 168-182.
    14. Papakostas, K. & Mavromatis, T. & Kyriakis, N., 2010. "Impact of the ambient temperature rise on the energy consumption for heating and cooling in residential buildings of Greece," Renewable Energy, Elsevier, vol. 35(7), pages 1376-1379.
    15. Li, Honglian & Huang, Jin & Hu, Yao & Wang, Shangyu & Liu, Jing & Yang, Liu, 2021. "A new TMY generation method based on the entropy-based TOPSIS theory for different climatic zones in China," Energy, Elsevier, vol. 231(C).
    16. Chen, Ji-Long & He, Lei & Chen, Qiao & Lv, Ming-Quan & Zhu, Hong-Lin & Wen, Zhao-Fei & Wu, Sheng-Jun, 2019. "Study of monthly mean daily diffuse and direct beam radiation estimation with MODIS atmospheric product," Renewable Energy, Elsevier, vol. 132(C), pages 221-232.
    17. Furlan, Claudia & de Oliveira, Amauri Pereira & Soares, Jacyra & Codato, Georgia & Escobedo, João Francisco, 2012. "The role of clouds in improving the regression model for hourly values of diffuse solar radiation," Applied Energy, Elsevier, vol. 92(C), pages 240-254.
    18. Ciprian Cristea & Maria Cristea & Dan Doru Micu & Andrei Ceclan & Radu-Adrian Tîrnovan & Florica Mioara Șerban, 2022. "Tridimensional Sustainability and Feasibility Assessment of Grid-Connected Solar Photovoltaic Systems Applied for the Technical University of Cluj-Napoca," Sustainability, MDPI, vol. 14(17), pages 1-23, August.
    19. Piotr Michalak, 2023. "Simulation and Experimental Study on the Use of Ventilation Air for Space Heating of a Room in a Low-Energy Building," Energies, MDPI, vol. 16(8), pages 1-17, April.
    20. Jiaxiang Lei & Honglian Li & Chengwang Li & Minrui Xu, 2023. "A New Method for Determining Outdoor Humidity Ratio of Natatorium in Transition Season," Energies, MDPI, vol. 16(7), pages 1-17, March.

    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:15:y:2022:i:23:p:8904-:d:983671. 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.