Calibrating Perez model coefficients using subset simulation

M. Meshkin Kiya, R.C.G.M. Loonen, R. Paolini, J.L.M. Hensen

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Abstract

The Perez sky diffuse model has been validated in many locations, however, studies have shown that the precision of estimation can be improved through localization of the model coefficients. This paper studies the effect of tuning Perez irradiance coefficients based on local information for estimating the incident solar radiation on tilted surfaces. The added value of a calibrated Perez model is highlighted by evaluating the heating and cooling energy needs of an office building. Calibration is performed by using Subset Simulation, i.e. a sampling technique based on Markov Chain Monte Carlo. The versatility of the Subset Simulation technique allows for handling multivariant calibration problems and is therefore suitable for finetuning Perez irradiance coefficients. Measurements of global horizontal, direct normal and diffuse horizontal solar irradiation, as well as the global solar irradiation on 90°, 30° and 15° tilted surfaces form the basis of the calibration. It is found that in the studied location, the default Perez model overestimates the incident solar radiation on vertical surfaces facing south. The calibrated coefficients are then embedded in the source code of EnergyPlus. Simulations with a reference office show that the effect of calibrating Perez coefficients can be significant, because it leads to approximately 12% difference in predicted annual cooling energy use and 9% difference in peak cooling loads, respectively.
Original languageEnglish
Title of host publicationProceedings of Solaris 2018
Place of PublicationBristol
PublisherInstitute of Physics
Pages1-6
DOIs
Publication statusPublished - 2019
Event9th edition of the international Solaris Conference - Chengdu, China
Duration: 30 Aug 201831 Aug 2018

Publication series

NameIOP Conference Series: Materials Science and Engineering
Volume556
ISSN (Print)1757-8981
ISSN (Electronic)1757-899X

Conference

Conference9th edition of the international Solaris Conference
CountryChina
CityChengdu
Period30/08/1831/08/18

Fingerprint

Incident solar radiation
Calibration
Cooling
Irradiation
Office buildings
Set theory
Markov processes
Tuning
Sampling
Heating

Keywords

  • Perez model
  • calibration
  • subset simulation
  • building energy

Cite this

Meshkin Kiya, M., Loonen, R. C. G. M., Paolini, R., & Hensen, J. L. M. (2019). Calibrating Perez model coefficients using subset simulation. In Proceedings of Solaris 2018 (pp. 1-6). [012017] (IOP Conference Series: Materials Science and Engineering; Vol. 556 ). Bristol: Institute of Physics. https://doi.org/10.1088/1757-899X/556/1/012017
Meshkin Kiya, M. ; Loonen, R.C.G.M. ; Paolini, R. ; Hensen, J.L.M. / Calibrating Perez model coefficients using subset simulation. Proceedings of Solaris 2018. Bristol : Institute of Physics, 2019. pp. 1-6 (IOP Conference Series: Materials Science and Engineering).
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abstract = "The Perez sky diffuse model has been validated in many locations, however, studies have shown that the precision of estimation can be improved through localization of the model coefficients. This paper studies the effect of tuning Perez irradiance coefficients based on local information for estimating the incident solar radiation on tilted surfaces. The added value of a calibrated Perez model is highlighted by evaluating the heating and cooling energy needs of an office building. Calibration is performed by using Subset Simulation, i.e. a sampling technique based on Markov Chain Monte Carlo. The versatility of the Subset Simulation technique allows for handling multivariant calibration problems and is therefore suitable for finetuning Perez irradiance coefficients. Measurements of global horizontal, direct normal and diffuse horizontal solar irradiation, as well as the global solar irradiation on 90°, 30° and 15° tilted surfaces form the basis of the calibration. It is found that in the studied location, the default Perez model overestimates the incident solar radiation on vertical surfaces facing south. The calibrated coefficients are then embedded in the source code of EnergyPlus. Simulations with a reference office show that the effect of calibrating Perez coefficients can be significant, because it leads to approximately 12{\%} difference in predicted annual cooling energy use and 9{\%} difference in peak cooling loads, respectively.",
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Meshkin Kiya, M, Loonen, RCGM, Paolini, R & Hensen, JLM 2019, Calibrating Perez model coefficients using subset simulation. in Proceedings of Solaris 2018., 012017, IOP Conference Series: Materials Science and Engineering, vol. 556 , Institute of Physics, Bristol, pp. 1-6, 9th edition of the international Solaris Conference, Chengdu, China, 30/08/18. https://doi.org/10.1088/1757-899X/556/1/012017

Calibrating Perez model coefficients using subset simulation. / Meshkin Kiya, M.; Loonen, R.C.G.M.; Paolini, R.; Hensen, J.L.M.

Proceedings of Solaris 2018. Bristol : Institute of Physics, 2019. p. 1-6 012017 (IOP Conference Series: Materials Science and Engineering; Vol. 556 ).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Meshkin Kiya M, Loonen RCGM, Paolini R, Hensen JLM. Calibrating Perez model coefficients using subset simulation. In Proceedings of Solaris 2018. Bristol: Institute of Physics. 2019. p. 1-6. 012017. (IOP Conference Series: Materials Science and Engineering). https://doi.org/10.1088/1757-899X/556/1/012017