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PV performance modelling: A review in the light of quality assurance for large PV plants.

Authors :
de la Parra, I.
Muñoz, M.
García, M.
Marcos, J.
Lorenzo, E.
Martínez-Moreno, F.
Source :
Renewable & Sustainable Energy Reviews. Oct2017, Vol. 78, p780-797. 18p.
Publication Year :
2017

Abstract

The quality assurance procedures associated with the financing of large PV plants are becoming increasingly more relevant to the PV scene in general. In this context, PV performance modelling is required in order to predict the energy yield and to rate the operating plant performance. Despite the availability of PV performance models since the early days of photovoltaics, the emergence of new proposals and the current debate on the development of an energy rating standard means that this can still be considered an open question. In the specific context of Quality Assurance Procedures, PV performance models must not only be accurate but must also be based on features specifically supported by manufacturers (datasheet information), in order to maintain the chain of responsibility in the event of failure. This paper reviews the currently available PV performance models with regard to accuracy and also compliance with datasheet specifications and guarantees. Accuracy is assessed through a meticulous measurement campaign conducted on PV arrays of four different technologies at a PV plant located in Navarra (northern Spain). The models reviewed are classified into physical models, based on the full I-V curve, and empirical models, which are solely based on the maximum power point (MPP). Despite the fact that physical models and MPP models with more than three parameters are currently widely used, this paper shows that empirical models with just three independent parameters suffice to accurately describe the relationship between PV array performance and operating conditions and are more easily derived from standard datasheet information. This result suggests that 3-parameter empirical models are the best option for PV performance modelling in the context of technical quality assurance procedures. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13640321
Volume :
78
Database :
Academic Search Index
Journal :
Renewable & Sustainable Energy Reviews
Publication Type :
Academic Journal
Accession number :
124142891
Full Text :
https://doi.org/10.1016/j.rser.2017.04.080