TY - JOUR
T1 - Analysis of indoor air temperature variation during semi-transparent photovoltaic power generation
T2 - Overcoming EnergyPlus model limitations
AU - Kim, Jiwon
AU - Kim, Naekyung
AU - Kwak, Younghoon
AU - Mun, Sunhye
N1 - Publisher Copyright:
© 2025 Elsevier Ltd
PY - 2025/10/1
Y1 - 2025/10/1
N2 - The purpose of this study was to analyze indoor air temperature variation during the operation of building-integrated semi-transparent photovoltaic (STPV) systems, focusing on the effects of heat transfer. During STPV power generation, absorbed solar energy that is not converted into electricity is transferred indoors in the form of heat. However, EnergyPlus does not simulate the transfer of heat generated by STPV systems to the interior. To overcome this problem, a custom algorithm was developed. Data were collected and analyzed using an STPV mock-up building. The proposed algorithm consists of three main parts. First, an indoor surface-temperature prediction model for each STPV cell type was developed using a multiple regression model. Second, Energy Management System custom control function of EnergyPlus was used to integrate the prediction model into the energy model. Third, the indoor heat transfer was calculated and incorporated into the energy model based on the predicted indoor surface and indoor air temperatures. The surface-temperature prediction model improved the prediction accuracy by 35.95 % and 20.82 % for crystalline and amorphous STPV modules, respectively. This methodology enables a more precise simulation of heat behavior during STPV power generation in buildings, contributing to the evaluation of building energy performance for sustainable building environments.
AB - The purpose of this study was to analyze indoor air temperature variation during the operation of building-integrated semi-transparent photovoltaic (STPV) systems, focusing on the effects of heat transfer. During STPV power generation, absorbed solar energy that is not converted into electricity is transferred indoors in the form of heat. However, EnergyPlus does not simulate the transfer of heat generated by STPV systems to the interior. To overcome this problem, a custom algorithm was developed. Data were collected and analyzed using an STPV mock-up building. The proposed algorithm consists of three main parts. First, an indoor surface-temperature prediction model for each STPV cell type was developed using a multiple regression model. Second, Energy Management System custom control function of EnergyPlus was used to integrate the prediction model into the energy model. Third, the indoor heat transfer was calculated and incorporated into the energy model based on the predicted indoor surface and indoor air temperatures. The surface-temperature prediction model improved the prediction accuracy by 35.95 % and 20.82 % for crystalline and amorphous STPV modules, respectively. This methodology enables a more precise simulation of heat behavior during STPV power generation in buildings, contributing to the evaluation of building energy performance for sustainable building environments.
KW - Building energy simulation (BES)
KW - Energy management system (EMS)
KW - EnergyPlus
KW - Indoor air temperature
KW - Semi-transparent photovoltaic (STPV)
UR - https://www.scopus.com/pages/publications/105008131492
U2 - 10.1016/j.jobe.2025.113140
DO - 10.1016/j.jobe.2025.113140
M3 - Article
AN - SCOPUS:105008131492
SN - 2352-7102
VL - 111
JO - Journal of Building Engineering
JF - Journal of Building Engineering
M1 - 113140
ER -