Improving the prediction performance of the finite element model for estimating the technical performance of the distributed generation of solar power system in a building façade

Choongwan Koo, Taehoon Hong, Jeongyoon Oh, Jun Ki Choi

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

As interest in the distributed generation of solar power system in a building façade continues to increase, its technical performance (i.e. the amount of electricity generation) should be carefully investigated before its implementation. In this regard, this study aimed to develop the nine-node-based finite element model for estimating the technical performance of the distributed generation of solar power system in a building façade (FEM9-node), focusing on the improvement of the prediction performance. The developed model (FEM9-node) was proven to be superior to the four-node-based model (FEM4-node), which was developed in the previous study, in terms of both prediction accuracy and standard deviation. In other words, the prediction accuracy (3.55%) and standard deviation (2.93%) of the developed model (FEM9-node) was determined to be superior to those of the previous model (FEM4-node) (i.e. 4.54% and 4.39%, respectively). The practical application was carried out to enable a decision maker (e.g. construction manager, facility manager) to understand how the developed model works in a clear way. It is expected that the developed model (FEM9-node) can be used in the early design phase in an easy way within a short time. In addition, it could be extended to any other countries in a global environment.

Original languageEnglish
Pages (from-to)41-53
Number of pages13
JournalApplied Energy
Volume215
DOIs
Publication statusPublished - 2018 Apr 1

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIP; Ministry of Science, ICT & Future Planning) ( NRF-2016R1C1B2007941 ).

Publisher Copyright:
© 2018 Elsevier Ltd

All Science Journal Classification (ASJC) codes

  • Building and Construction
  • Mechanical Engineering
  • Energy(all)
  • Management, Monitoring, Policy and Law

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