In this paper, a novel approach is proposed to capture the GHI conveniently and accurately. In traditional approaches, the local GHI can be measured with very expensive instruments, and the large-area GHI collection depends on complex satellite-based models, solargis algorithms, and the high-performance computers (HPC). Global horizontal irradiance (GHI) is a critical index to indicate the output power of the photovaltaic (PV). In particular, increasing the output of distributed solar power systems on cloudy days is important to developing solar-powered home fueling and charging systems for hydrogen-powered fuel-cell electric and battery-powered vehicles, respectively, because it reduces the system size and cost for solar power systems that are designed to have sufficient energy output on the worst (cloudy) days. Improving the harvesting of solar energy on cloudy days deserves wider attention due to increasing efforts to utilize renewable solar energy. These results are consistent with the solar tracking algorithm optimized for cloudy conditions that we proposed in an earlier report and that was based on a much smaller data set. On an annual basis the increase is predicted to be much less, typically only about 1%, because the contribution of cloudy days to the total annual solar energy captured by a photovoltaic system is small. During cloudy periods, we found that an H configuration increased the solar energy capture by nearly 40% compared to a DTS configuration during the same period, and we estimate the solar energy increase of an H configuration over a system that tracks the obscured solar disk could reach 50% over a whole heavily-overcast day. The dependence of the H/DTS ratio on the solar-collector tilt angle was in approximate agreement with the Isotropic Diffuse Model derived for heavily overcast conditions. Another set of solar collectors always had an H orientation, and this best captured the diffuse component of the solar radiation that predominates on cloudy days. In particular, a DTS orientation was found to capture up to twice as much solar energy as a horizontal (H) orientation in which the array is tilted toward the zenith. We found that on sunny days, solar collectors with a DTS configuration captured more solar energy in accordance with the well-known cosine dependence for the response of a flat-surfaced solar collector to the angle of incidence with direct beam radiation. These solar collectors thus captured the direct more » beam component of the solar radiation that predominates on sunny days. One set of solar collectors was always approximately pointed directly toward the sun (DTS) for a period around solar noon. The study included a variety of ambient conditions including different seasons and both cloudy and cloud-free conditions. This report analyzes an extensive set of measurements of the solar irradiance made using four identical solar arrays and associated solar sensors (collectively referred to as solar collectors) with different tilt angles relative to the earth's surface, and thus the position of the sun, in order to determine an optimal tracking algorithm for capturing solar radiation.
An implicit clear-sky bias may hinder efforts to quantitatively understand and improve representation of aerosol–cloud interactions, which remain dominant uncertainties in models. In the eastern US, relative humidity alone cannot explain differences in ALW, suggesting that emissions and in situ chemistry related to anthropogenic sources exert determining impacts. Cloudy and clear-sky periods exhibit significant differences more » in PM 2.5 mass and chemical composition that vary regionally and seasonally. We examine surface PM 2.5 chemical constituent concentrations in the Interagency Monitoring of PROtected Visual Environments (IMPROVE) network in the United States during cloudy and clear-sky times defined using Moderate Resolution Imaging Spectroradiometer (MODIS) cloud flags from 2010 to 2014 with a focus on differences in particle species that affect hygroscopicity and aerosol liquid water (ALW).
Cloud-affected satellite retrievals are subject to higher uncertainty and are often removed from data products, hindering quantitative estimates of tropospheric chemical composition during cloudy times. Clouds are prevalent and alter fine particulate matter (PM 2.5) mass and chemical composition.
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