Parameter Calibration for a TRNSYS BIPV Model Using In Situ Test Data

Sang-Woo Ha, Seung-Hoon Park, Jae-Yong Eom, Min-Suk Oh, Ga-Young Cho and Eui-Jong Kim
Additional contact information
Sang-Woo Ha: Department of Architectural Engineering, Inha University, Incheon 22212, Korea
Seung-Hoon Park: Department of Architectural Engineering, Inha University, Incheon 22212, Korea
Jae-Yong Eom: R&D Division, EAGON Windows&Doors Co., Ltd., Incheon 22107, Korea
Min-Suk Oh: R&D Division, DAEJIN, Seoul 05839, Korea
Ga-Young Cho: Department of Smart City Research, Seoul Institute of Technology, Seoul 03909, Korea
Eui-Jong Kim: Department of Architectural Engineering, Inha University, Incheon 22212, Korea

Energies, 2020, vol. 13, issue 18, 1-15

Abstract: Installing renewable energy systems for zero-energy buildings has become increasingly common; building integrated photovoltaic (BIPV) systems, which integrate PV modules into the building envelope, are being widely selected as renewable systems. In particular, owing to the rapid growth of information and communication technology, the requirement for appropriate operation and control of energy systems has become an important issue. To meet these requirements, a computational model is essential; however, some unmeasurable parameters can result in inaccurate results. This work proposes a calibration method for unknown parameters of a well-known BIPV model based on in situ test data measured over eight days; this parameter calibration was conducted via an optimization algorithm. The unknown parameters were set such that the results obtained from the BIPV simulation model are similar to the in situ measurement data. Results of the calibrated model indicated a root mean square error (RMSE) of 3.39 °C and 0.26 kW in the BIPV cell temperature and total power production, respectively, whereas the noncalibrated model, which used typical default values for unknown parameters, showed an RMSE of 6.92 °C and 0.44 kW for the same outputs. This calibration performance was quantified using measuring data from the first four days; the error increased slightly when data from the remaining four days were compared for the model tests.

Keywords: BIPV; model parameter calibration; particle swarm optimization; TRNSYS (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: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/1996-1073/13/18/4935/pdf (application/pdf)
https://www.mdpi.com/1996-1073/13/18/4935/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:13:y:2020:i:18:p:4935-:d:416417

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().