Expanding PVLIB Python for Modeling Static CPV Systems

Moreno, Marcos, Steinbach, Inia, Haas, Sabine, Askins, Stephen A, Herrero Martin, Rebeca ORCID: https://orcid.org/0000-0003-4309-6084, Anton Hernandez, Ignacio ORCID: https://orcid.org/0000-0002-6890-5477, Anglade, Laetitia, Ackermann, Mathieu and Dominguez Dominguez, Cesar ORCID: https://orcid.org/0000-0002-2751-7208 (2019). Expanding PVLIB Python for Modeling Static CPV Systems. In: "13th PVPMC Workshop KunSha", 08/12/2019 - 13/12/2019, KunShan, China. pp. 1-2.


Title: Expanding PVLIB Python for Modeling Static CPV Systems
Item Type: Presentation at Congress or Conference (Article)
Event Title: 13th PVPMC Workshop KunSha
Event Dates: 08/12/2019 - 13/12/2019
Event Location: KunShan, China
Title of Book: Proccedings 13th PVPMC Workshop KunShan
Date: 2019
Faculty: Instituto de Energía Solar (IES) (UPM)
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Concentrator Photovoltaics (CPV) has shown very high conversion efficiencies (> 40%) but suffers from a major limitation: it has to employ very precise external two-axis tracking structures to align the modules to the direct irradiance, which highly increase installation costs and prevents their use on rooftop applications. The Swiss company Insolight has developed a CPV system with integrated planar microtracking enabling its installation on a fixed structure without the need an external moving tracker, which is compatible with rooftop applications. The module uses III-V multi-junction solar cells under concentration and a size close to 1 mm, which reduces the form factor to a few centimeters. A 29% module efficiency at Concentrator Standard Test Conditions (IEC 62670-1) has been demonstrated outdoors, which can lead to a large gain in energy yield. Some challenges remain, like the optimization of the optical system to collect very wide angles of incidence.

Funding Projects

Horizon 2020
Fostering a Next Generation of European Photovoltaic Society through Open Science

More information

Item ID: 67194
DC Identifier: https://oa.upm.es/67194/
OAI Identifier: oai:oa.upm.es:67194
Deposited by: Memoria Investigacion
Deposited on: 27 Apr 2022 11:52
Last Modified: 27 Apr 2022 11:52
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