Modeling Outdoor Service Lifetime Prediction of PV Modules: Effects of Combined Climatic Stressors on PV Module Power Degradation

Kaaya, Ismail; Koehl, Michael; Mehilli, Amantin Panos; Mariano, Sidrach de Cardona; Weiss, Karl Anders

doi:10.1109/jphotov.2019.2916197

Cited by 64 publications

(57 citation statements)

References 18 publications

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“…In ref. [10], three degradation processes are defined and empirically expressed due to the combination of climate degradation factors: Hydrolysis-degradation ( ) related to the effect of temperature and humidity, photo-degradation ( ) depends on temperature,…”

Section: Spatial Distribution Of Pv Degradation Ratesmentioning

confidence: 99%

“…In ref. [10], three degradation processes are defined and empirically expressed due to the combination of climate degradation factors: Hydrolysis-degradation (k H ) related to the effect of temperature and humidity, photo-degradation (k P ) depends on temperature, humidity and UV irradiance, and thermo-mechanical-degradation (k Tm ) due to high temperature and temperature differences. The models are presented in Equations (11) to (14):…”

Section: Spatial Distribution Of Pv Degradation Ratesmentioning

confidence: 99%

“…where the parameters are: The degradation mechanisms are quantified by using the fitting coefficients published in ref. [10] for a high-performance monocrystalline silicon PV module installed in the open-rack mounting configuration.…”

Section: Spatial Distribution Of Pv Degradation Ratesmentioning

confidence: 99%

“…For example, while in deserts the risk of sand-storms is high, in highlands wind gusts and snow loads can damage the PV installations. Important findings and calculation methods about the climatic triggers of degradation modes under different climate zones have been presented in [3][4][5][6][7][8][9][10][11]. Irradiation, temperature, and humidity have been identified as the main degradation precursors, leading to different degradation mechanisms depending on the stress level in each climate zone.…”

Section: Introductionmentioning

confidence: 99%

“…However, it is known that the impact of climate on material properties and energy production will vary over time and location. Interesting approaches to calculate the degradation rates have been proposed in references [10,15]. Both models consider as main climate degradation factors the average temperatures, temperature changes, humidity, and ultraviolet (UV) irradiation, which is in line with indoor testing and standards for PV reliability.…”

Section: Introductionmentioning

confidence: 99%

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Global Climate Data Processing and Mapping of Degradation Mechanisms and Degradation Rates of PV Modules

et al. 2019

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Photovoltaic (PV) systems are the cheapest source of electricity in sunny locations and nearly all European countries. However, the fast deployment of PV systems around the world is bringing uncertainty to the PV community in terms of the reliability and long-term performance of PV modules under different climatic stresses, such as irradiation, temperature changes, and humidity. Methodologies and models to estimate the annual degradation rates of PV modules have been studied in the past, yet, an evaluation of the issue at global scale has not been addressed so far. Hereby, we process the ERA5 climate re-analysis dataset to extract and model the climatic stresses necessary for the calculation of degradation rates. These stresses are then applied to evaluate three degradation mechanisms (hydrolysis-degradation, thermomechanical-degradation, and photo-degradation) and the total degradation rate of PV modules due to the combination of temperature, humidity, and ultraviolet irradiation. Further on, spatial distribution of the degradation rates worldwide is computed and discussed proving direct correlation with the Köppen-Geiger-Photovoltaic climate zones, showing that the typical value considered for the degradation rate on PV design and manufacturer warranties (i.e., 0.5%/a) can vary ± 0.3%/a in the temperate zones of Europe and rise up to 1.5%/a globally. The mapping of degradation mechanisms and total degradation rates is provided for a monocrystalline silicon PV module. Additionally, we analyze the temporal evolution of degradation rates, where a global degradation rate is introduced and its dependence on global ambient temperature demonstrated. Finally, the categorization of degradation rates is made for Europe and worldwide to facilitate the understanding of the climatic stresses.

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Section: Spatial Distribution Of Pv Degradation Ratesmentioning

confidence: 99%

Section: Spatial Distribution Of Pv Degradation Ratesmentioning

confidence: 99%

Section: Spatial Distribution Of Pv Degradation Ratesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Global Climate Data Processing and Mapping of Degradation Mechanisms and Degradation Rates of PV Modules

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Drivers for the cracking of multilayer polyamide‐based backsheets in field photovoltaic modules: In‐depth degradation mapping analysis

Fairbrother

Gong

et al. 2020

Progress in Photovoltaics

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There's a lack of understanding on the root cause of cracking of photovoltaic (PV) backsheets due to the challenge of multilayer characterization and the complicated failure modes at the sub-module level. In this work, in-depth degradation mapping of field-exposed polyamide-based (PA-based) PV module backsheets was studied, with the major focus on the identification of underlying drivers for the through cracking (in between the solar cells). PV modules were retrieved from five different locations, comprising a variety of climates, including humid subtropical, hot-summer Mediterranean, tropical savanna climate and hot arid. A suite of microscale cross-sectional characterizations, including chemical changes, fluorescence intensity, and modulus as a function of distance from the air surface of the backsheet, were performed. Results showed more advanced signs of degradation of the inner layer than the outer layer in the cracking region. Increases in the modulus was identified as the major indicator for the cracking. Moreover, a rudimentary test by immersion in acetic acid, which forms during photodegradation of the ethylene-vinyl acetate copolymer (EVA) encapsulant, showed the first-time direct evidence that acetic acid can largely accelerate the chemical degradation and facilitate the cracking of PA inner layer. This study suggests that the field cracking of PA-based backsheet can be attributed to the combined effects of chemical degradation and physical reorganization (chemi-crystallization) under cyclic thermomechanical stresses. Therefore, it is important to consider effects of local

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Photovoltaic lifetime forecast model based on degradation patterns

Kaaya

Lindig

Weiß

et al. 2020

Progress in Photovoltaics

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The ever‐growing secondary market of photovoltaic (PV) systems (i.e., the transaction of solar plants ownership) calls for reliable and high‐quality long‐term PV degradation forecasts to mitigate the financial risks. However, when long‐term PV performance degradation forecasts are required after a short time with limited degradation history, the existing physical and data‐driven methods often provide unrealistic degradation scenarios. Therefore, we present a new data‐driven method to forecast PV lifetime after a small performance degradation of only 3%. To achieve an accurate and reliable forecast, the developed method addresses the fundamental challenges that usually affect long‐term degradation evaluation such as data treatment, choosing a good degradation model, and understanding the different degradation patterns. In the paper, we propose and describe an algorithm for degradation trend evaluation, a new concept of multiple “time‐ and degradation pattern‐dependent” degradation factors. The proposed method has been calibrated and validated using different PV modules and systems data of 5 to 35 years of field exposure. The model has been benchmarked against existing statistical models evaluating 11 experimental PV systems with different technologies. The key advantage of our model over statistical ones is the ability to perform more reliable forecasts with limited degradation history. With an average relative uncertainty of 7.0%, our model is outstanding in consistency for different forecasting time horizons. Moreover, the model is applicable to all PV technologies. The proposed method will aid in making reliable financial decisions and also in adequately planning operation and maintenance activities.

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Modeling Outdoor Service Lifetime Prediction of PV Modules: Effects of Combined Climatic Stressors on PV Module Power Degradation

Cited by 64 publications

References 18 publications

Global Climate Data Processing and Mapping of Degradation Mechanisms and Degradation Rates of PV Modules

Global Climate Data Processing and Mapping of Degradation Mechanisms and Degradation Rates of PV Modules

Drivers for the cracking of multilayer polyamide‐based backsheets in field photovoltaic modules: In‐depth degradation mapping analysis

Photovoltaic lifetime forecast model based on degradation patterns

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