Developing particle-based models to predict solar energy attenuation using long-term daily remote and local measurements

Abstract

Iran has an annual average of 2.8–5.4 kW h/m2d of radiation and has a high capacity for extracting electricity from its solar resources. Tehran, the capital of Iran, is one of the most polluted cities in the world in terms of atmospheric aerosols. Due to the rising air pollution in Tehran, the existing research is outdated. An analysis of the loss of electricity generation due to particulates can significantly affect the feasibility of a photovoltaic power plant in Tehran. Several factors affect the electricity generation of photovoltaic systems. The most critical is solar radiation. The amount of solar radiation transmitted and, ultimately, the amount of electricity generated depends on several atmospheric factors. One of the most important factors is the concentration of suspended particles of different sizes. In the present work, linear models based on observed suspended particle concentrations, including PM10 and PM2.5, have been proposed for Tehran from 2014 to 2020 to anticipate the aerosol attenuation index due to aerosols. Based on the correlation coefficient values (R), in the first and last months of the year, November, December, and January, the models performed better to predict the aerosol attenuation index based on PM2.5. The R values were, in order, 0.1553, 0.2926, and 0.1341. As remote measurements, the NASA CERES syn 1-deg product parameters and, as ground observations, Surface Solar Radiation (SSR) and PM10 and PM2.5 concentrations were used to estimate the impacts of aerosols on radiation. With the help of the CERES syn 1-deg product, it is declared that, on average, 8.30% of the total radiation received was wasted due to the presence of aerosols. Considering observed SSR, CERES syn 1-deg product performance was validated, with RMSE and MBD values of 14.09% and 10.89%, respectively.