4.6 Article

Photovoltaic performance assess by correcting the I-V curves in outdoor tests

期刊

SOLAR ENERGY
卷 237, 期 -, 页码 11-18

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.solener.2022.03.064

关键词

Outdoor tests; Photovoltaic performance; I-V curves; STC; NOCT; Temperature coefficients

资金

  1. Colombia's Ministry of Science, Technology and Innovation (MINCIENCIAS) [727-2015, FP44842-124-2017]
  2. Colombia Scientific Program [FP44842-218-2018]

向作者/读者索取更多资源

This study translates outdoor photovoltaic performance to standard test conditions (STC) or other power rating conditions by combining different I-V curves and weather data. The generated dataset covers a wide range of outdoor performance behavior as a function of irradiance and temperature, ensuring reliability in the estimation. Filtering and extrapolation techniques are used to improve estimation accuracy, achieving relative errors of less than 8% compared to datasheet values.
The photovoltaic performance is conventionally defined at Standard Test Conditions (STC), considering mainly an irradiance of 1000 W/m(2) and device temperature of 25 degrees C. Nevertheless, outdoor conditions involve additional variables, including their transient behavior, affecting the performance. Therefore, measuring the performance at STC in outdoor tests is not always possible. In order to estimate the performance at STC or other power rating conditions such as the Nominal Operating Cell Temperature (NOCT), this work translated the outdoor performance at the target conditions by combining three different I-V curves and corresponding weather data for three photovoltaic technologies. Hence, a random process was proposed to generate the dataset to be translated, ensuring reliability in the estimation due to the significant number of considered weather conditions combinations, covering a wide range of the outdoor performance behavior as a function of irradiance and temperature. Besides, the dataset was filtered using an irradiance and extrapolation range, improving the estimation by calculating relative error of less than 8% at STC and NOCT concerning the datasheet values. Finally, the procedure was extended to estimate the temperature coefficients allowing a complete performance validation concerning the datasheet.

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