Nonlinear Photovoltaic Degradation Rates: Modeling and Comparison Against Conventional Methods

Journal Article · Mon May 18 00:00:00 EDT 2020 · IEEE Journal of Photovoltaics

DOI:https://doi.org/10.1109/JPHOTOV.2020.2992432· OSTI ID:1634784

Theristis, Marios  ^[1]; Livera, Andreas  ^[2]; Jones, C. Birk  ^[1]; Makrides, George ^[2]; Georghiou, George E.  ^[2]; Stein, Joshua S.  ^[1]

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1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2. Univ. of Cyprus (Cyprus)

Although common practice for estimating photovoltaic (PV) degradation rate (RD) assumes a linear behavior, field data have shown that degradation rates are frequently nonlinear. This article presents a new methodology to detect and calculate nonlinear RD based on PV performance time-series from nine different systems over an eight-year period. Prior to performing the analysis and in order to adjust model parameters to reflect actual PV operation, synthetic datasets were utilized for calibration purposes. A change-point analysis is then applied to detect changes in the slopes of PV trends, which are extracted from constructed performance ratio (PR) time-series. Once the number and location of change points is found, the ordinary least squares method is applied to the different segments to compute the corresponding rates. The obtained results verified that the extracted trends from the PR time-series may not always be linear and therefore, “nonconventional” models need to be applied. All thin-film technologies demonstrated nonlinear behavior whereas nonlinearity detected in the crystalline silicon systems is thought to be due to a maintenance event. A comparative analysis between the new methodology and other conventional methods demonstrated levelized cost of energy differences of up to 6.14%, highlighting the importance of considering nonlinear degradation behavior

• Research Organization: Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office
• Grant/Contract Number: AC04-94AL85000
• OSTI ID: 1634784
• Report Number(s): SAND2020-3982J; 685295
• Journal Information: IEEE Journal of Photovoltaics, Vol. 10, Issue 4; ISSN 2156-3381
• Publisher: IEEE
• Country of Publication: United States
• Language: English

Related Subjects

14 SOLAR ENERGY