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Influences of environmental factors on Si-based photovoltaic modules after longtime outdoor exposure by multiple regression analysis

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  • Chantana, Jakapan
  • Kamei, Aika
  • Minemoto, Takashi

Abstract

Degradation of Si-based photovoltaic (PV) modules after longtime outdoor exposure is quantitatively investigated using multiple regression analysis. Performance ratios (PR) of the PV modules are primarily influenced not only by irradiation intensity on tilted surface (IrrT), average photon energy (APE), and module temperature (Tmod) but also by angle of incidence (AOI). It is demonstrated that multiple regression analysis allows us to independently and quantitatively identify how each IrrT, APE, Tmod, or AOI (environmental factors) relates to the PR (outcome), thus leading to the understanding of impacts of environmental factors on physical properties of the Si-based PV modules. After longtime outdoor exposure, the influences of IrrT, APE, and AOI on the PR of multi-crystalline (mc-Si) and single-crystalline (c-Si) modules are severely increased, resulting from the decay of interconnection and discoloration of ethylene vinyl acetate films. The dependences of environmental factors on the PR of hydrogenated amorphous (a-Si) modules do not change as much as those on PR of mc-Si and c-Si modules do because of differences in the module structures.

Suggested Citation

  • Chantana, Jakapan & Kamei, Aika & Minemoto, Takashi, 2017. "Influences of environmental factors on Si-based photovoltaic modules after longtime outdoor exposure by multiple regression analysis," Renewable Energy, Elsevier, vol. 101(C), pages 10-15.
    • Handle: RePEc:eee:renene:v:101:y:2017:i:c:p:10-15
    DOI: 10.1016/j.renene.2016.08.037
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    References listed on IDEAS

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    1. Chantana, Jakapan & Ueno, Seiya & Ota, Yasuyuki & Nishioka, Kensuke & Minemoto, Takashi, 2015. "Uniqueness verification of direct solar spectral index for estimating outdoor performance of concentrator photovoltaic systems," Renewable Energy, Elsevier, vol. 75(C), pages 762-766.
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    Cited by:

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    2. Mateo, C. & Hernández-Fenollosa, M.A. & Montero, Á. & Seguí-Chilet, S., 2018. "Analysis of initial stabilization of cell efficiency in amorphous silicon photovoltaic modules under real outdoor conditions," Renewable Energy, Elsevier, vol. 120(C), pages 114-125.
    3. Cogoljević, Dušan & Gavrilović, Milan & Roganović, Miloš & Matić, Ivana & Piljan, Ivan, 2018. "Analyzing of consumer price index influence on inflation by multiple linear regression," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 941-944.
    4. Chantana, Jakapan & Mano, Hiroyuki & Horio, Yuhei & Hishikawa, Yoshihiro & Minemoto, Takashi, 2017. "Spectral mismatch correction factor indicated by average photon energy for precise outdoor performance measurements of different-type photovoltaic modules," Renewable Energy, Elsevier, vol. 114(PB), pages 567-573.
    5. Jyoti U. Devkota, 2020. "Structural Equation Modeling in Forecasting Satisfaction of Biogas to a Rural Household: Examples from Nepal," Biophysical Economics and Resource Quality, Springer, vol. 5(4), pages 1-13, December.
    6. Neves, Guilherme & Vilela, Waldeir & Pereira, Enio & Yamasoe, Marcia & Nofuentes, Gustavo, 2021. "Spectral impact on PV in low-latitude sites: The case of southeastern Brazil," Renewable Energy, Elsevier, vol. 164(C), pages 1306-1319.
    7. Yadav, Amit Kumar & Chandel, S.S., 2017. "Identification of relevant input variables for prediction of 1-minute time-step photovoltaic module power using Artificial Neural Network and Multiple Linear Regression Models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 955-969.
    8. Imai, Yurie & Chantana, Jakapan & Kawano, Yu & Hishikawa, Yoshihiro & Minemoto, Takashi, 2019. "Description of performance degradation of photovoltaic modules using spectral mismatch correction factor under different irradiance levels," Renewable Energy, Elsevier, vol. 141(C), pages 444-450.

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