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

Serena Summa (), Giada Remia, Ambra Sebastianelli, Gianluca Coccia and Costanzo Di Perna
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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

Energies, 2022, vol. 15, issue 23, 1-18

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.

Keywords: EN ISO 52016-1; EN ISO 52010-1; solar irradiance decomposition and trasposition models; climate data; building simulation; building energy performance (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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