Adapting the Durisch model for bifacial silicon and high concentration multijunction photovoltaic modules efficiency prediction

Caio Felippe Abe, Gilles Notton, Ghjuvan-Antone Faggianelli, João Batista Dias and Paulo Roberto Wander

Renewable Energy, 2025, vol. 238, issue C

Abstract: Efficiency models are valuable tools for predicting the performance of photovoltaic (PV) systems. By providing expected efficiency based on operating conditions, they enable comparison with actual measured efficiency. Significant discrepancies between predicted and measured values can indicate operational issues, such as measurement errors or equipment defects. This study focuses on the Durisch model, a widely used and consolidated efficiency model. We adapted the model to describe the efficiency of bifacial and high concentration multijunction devices (HCPV), incorporating different components of solar radiation. Our approach was validated using an extensive experimental setup with four distinct PV module types. Data filtering methods are discussed, and the normalized root mean square error (nRMSE) for the model with less restrictive filtering was 3.43 %, 2.42 %, 3.33 %, and 7.32 % for polycrystalline, monocrystalline, bifacial, and HCPV PV arrays, respectively. Different factors contribute to a relatively higher error for the HCPV array efficiency modeling, such as: the HCPV array's response to the beam irradiance only; the 90-m distance between the beam irradiance meter and the HCPV array; the HCPV array's sensitiveness to errors on tracking due to the use of concentrators; and the beam irradiance's changing more rapidly than the global irradiance.

Keywords: photovoltaic efficiency model; PV system performance; PV tracker; Data filtering (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148124021025
Full text for ScienceDirect subscribers only

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:eee:renene:v:238:y:2025:i:c:s0960148124021025

DOI: 10.1016/j.renene.2024.122034

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().