Assessment of flat, symmetric, and asymmetric CPC photovoltaic thermal air solar collectors for building façades using artificial Neural Network Modelling
This study aims to develop and evaluate the performance of an asymmetric compound parabolic concentrator (ACPC) PV/T designed for building fa & ccedil;ade configuration, addressing the limitations of conventional symmetric compound parabolic concentrators (CPC) and flat type, double-pass photovo...
Published in: | JOURNAL OF BUILDING ENGINEERING |
---|---|
Main Authors: | , , , , , , , , |
Format: | Article |
Language: | English |
Published: |
ELSEVIER
2024
|
Subjects: | |
Online Access: | https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001352977200001 |
author |
Roshdan Wan Nur Adilah Wan; Jarimi Hasila; Al-Waeli Ali H. A.; Razak Tajul Rosli; Ahmad Emy Zairah; Syafiq Ubaidah; Ibrahim Adnan; Sopian Kamaruzzaman |
---|---|
spellingShingle |
Roshdan Wan Nur Adilah Wan; Jarimi Hasila; Al-Waeli Ali H. A.; Razak Tajul Rosli; Ahmad Emy Zairah; Syafiq Ubaidah; Ibrahim Adnan; Sopian Kamaruzzaman Assessment of flat, symmetric, and asymmetric CPC photovoltaic thermal air solar collectors for building façades using artificial Neural Network Modelling Construction & Building Technology; Engineering |
author_facet |
Roshdan Wan Nur Adilah Wan; Jarimi Hasila; Al-Waeli Ali H. A.; Razak Tajul Rosli; Ahmad Emy Zairah; Syafiq Ubaidah; Ibrahim Adnan; Sopian Kamaruzzaman |
author_sort |
Roshdan |
spelling |
Roshdan, Wan Nur Adilah Wan; Jarimi, Hasila; Al-Waeli, Ali H. A.; Razak, Tajul Rosli; Ahmad, Emy Zairah; Syafiq, Ubaidah; Ibrahim, Adnan; Sopian, Kamaruzzaman Assessment of flat, symmetric, and asymmetric CPC photovoltaic thermal air solar collectors for building façades using artificial Neural Network Modelling JOURNAL OF BUILDING ENGINEERING English Article This study aims to develop and evaluate the performance of an asymmetric compound parabolic concentrator (ACPC) PV/T designed for building fa & ccedil;ade configuration, addressing the limitations of conventional symmetric compound parabolic concentrators (CPC) and flat type, double-pass photovoltaic thermal (PV/T) air solar collectors. The ACPC enhances solar incidence angle within the full acceptance angle for optimal performance in a fa & ccedil;ade configuration. However, accurately predicting the performance of the solar collectors remains a challenge due to the variations in ambient parameters. To overcome this, an Artificial Neural Network (ANN) model was developed and validated to predict system performance based on input ambient variables, such as solar radiation and temperature, with outputs representing the electrical and thermal performance of the PV/T collector. The validated ANN model was then used to conduct a simulation case study for the tropical climate of Malaysia. The simulation results demonstrated that the ACPC PV/T collector outperformed both symmetric CPC and flat-type PV/T collectors regarding electrical and thermal performance. Additionally, the ACPC PV/T had a shorter payback of 5.4 years, approximately 1 year shorter than the CPC and 2 years shorter than the flattype PV/T. These findings suggest that the ACPC PV/T system offers a more efficient and costeffective solution for fa & ccedil;ade-integrated systems. This study contributes to the body of knowledge on photovoltaic/thermal systems with three key contributions: first, an investigation of the underexplored asymmetric CPC for building fa & ccedil;ades; second, the utilization of a data-driven ANN model as a predictive tool, demonstrated through a simulation case study in combination with TRNSYS; and third, a comparative analysis of asymmetric CPC, symmetric CPC, and flat PV/T air solar collectors specifically for fa & ccedil;ade applications. This study, therefore, provides a comprehensive platform for further research on CPC PV/T systems for building fa & ccedil;ades. ELSEVIER 2352-7102 2024 98 10.1016/j.jobe.2024.111221 Construction & Building Technology; Engineering WOS:001352977200001 https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001352977200001 |
title |
Assessment of flat, symmetric, and asymmetric CPC photovoltaic thermal air solar collectors for building façades using artificial Neural Network Modelling |
title_short |
Assessment of flat, symmetric, and asymmetric CPC photovoltaic thermal air solar collectors for building façades using artificial Neural Network Modelling |
title_full |
Assessment of flat, symmetric, and asymmetric CPC photovoltaic thermal air solar collectors for building façades using artificial Neural Network Modelling |
title_fullStr |
Assessment of flat, symmetric, and asymmetric CPC photovoltaic thermal air solar collectors for building façades using artificial Neural Network Modelling |
title_full_unstemmed |
Assessment of flat, symmetric, and asymmetric CPC photovoltaic thermal air solar collectors for building façades using artificial Neural Network Modelling |
title_sort |
Assessment of flat, symmetric, and asymmetric CPC photovoltaic thermal air solar collectors for building façades using artificial Neural Network Modelling |
container_title |
JOURNAL OF BUILDING ENGINEERING |
language |
English |
format |
Article |
description |
This study aims to develop and evaluate the performance of an asymmetric compound parabolic concentrator (ACPC) PV/T designed for building fa & ccedil;ade configuration, addressing the limitations of conventional symmetric compound parabolic concentrators (CPC) and flat type, double-pass photovoltaic thermal (PV/T) air solar collectors. The ACPC enhances solar incidence angle within the full acceptance angle for optimal performance in a fa & ccedil;ade configuration. However, accurately predicting the performance of the solar collectors remains a challenge due to the variations in ambient parameters. To overcome this, an Artificial Neural Network (ANN) model was developed and validated to predict system performance based on input ambient variables, such as solar radiation and temperature, with outputs representing the electrical and thermal performance of the PV/T collector. The validated ANN model was then used to conduct a simulation case study for the tropical climate of Malaysia. The simulation results demonstrated that the ACPC PV/T collector outperformed both symmetric CPC and flat-type PV/T collectors regarding electrical and thermal performance. Additionally, the ACPC PV/T had a shorter payback of 5.4 years, approximately 1 year shorter than the CPC and 2 years shorter than the flattype PV/T. These findings suggest that the ACPC PV/T system offers a more efficient and costeffective solution for fa & ccedil;ade-integrated systems. This study contributes to the body of knowledge on photovoltaic/thermal systems with three key contributions: first, an investigation of the underexplored asymmetric CPC for building fa & ccedil;ades; second, the utilization of a data-driven ANN model as a predictive tool, demonstrated through a simulation case study in combination with TRNSYS; and third, a comparative analysis of asymmetric CPC, symmetric CPC, and flat PV/T air solar collectors specifically for fa & ccedil;ade applications. This study, therefore, provides a comprehensive platform for further research on CPC PV/T systems for building fa & ccedil;ades. |
publisher |
ELSEVIER |
issn |
2352-7102 |
publishDate |
2024 |
container_volume |
98 |
container_issue |
|
doi_str_mv |
10.1016/j.jobe.2024.111221 |
topic |
Construction & Building Technology; Engineering |
topic_facet |
Construction & Building Technology; Engineering |
accesstype |
|
id |
WOS:001352977200001 |
url |
https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001352977200001 |
record_format |
wos |
collection |
Web of Science (WoS) |
_version_ |
1818940501186838528 |