Studying Solar Irradiance Variability and Solar Energy Using Geostationary Satellite Products and Ground Measurements

Date

2018

Authors

Xia, Shuang

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Abstract

Solar radiation is the most abundant source of energy. Measuring solar irradiance from satellites is becoming important in the field of renewable energy, when planning for photovoltaic (PV) or thermal systems. Satellites can provide long-term solar irradiance data in a large field of view compared to ground observations, although ground–based equipment can acquire data with much higher temporal resolution. Comparison of satellite estimation of shortwave downward radiative flux at the surface (Gs) against global horizontal irradiance from the ground (Gg) is important and necessary if satellite estimates are going to be used for applications in solar mapping and electricity grid integration. The amount of solar radiation reaching the earth’s surface varies greatly because of changing atmospheric conditions. Clouds play a major role in regulating the amount of solar irradiance reaching the Earth’s surface. It is essential to determine how solar irradiance varies with different cloud types and heights. Mapping solar energy is useful for adding solar power into power grid portfolios and the placement of solar PV system.

This dissertation consists of three interrelated studies: (1) a validation of Gs from Geostationary Operational Environmental Satellite (GOES) Surface and Insolation Products (GSIP) using Gg from two ground stations, one in the main campus of the University of Texas at San Antonio (UTSA) and the other in the Alamo Solar Farm of San Antonio (ASF); (2) a study on how solar variability relates to different cloud types and heights from GOES GSIP in the San Antonio area; and (3) an investigation the of the spatial variability of cloudiness and solar energy climatological conditions over Texas and surrounding regions based on GOES GSIP.

Satellite-derived Gs is found to be significantly (p-value<0.05) correlated with Gg at the two San Antonio locations under all sky conditions, clear-sky conditions, and cloud-sky conditions. Correlations under different cloud types (partly, water, mixed, glaciated, cirrus and multilayered) and different cloud layers (low, mid and high) are generally greater than 0.60. The most frequent clouds found in the San Antonio area are water clouds, followed by cirrus clouds. The overall good agreement of the satellite estimates with the ground observations underscores the usefulness of the GOES surface solar irradiance estimates for solar energy studies in the San Antonio area. It enables us to better understand features of different types and layers of clouds and the time when clouds are likely to occur locally in San Antonio.

In the second part, a new variability index (VInew) having a better physical base than the one used in previous studies (VI) is introduced. The VInew performs better at all different time intervals than VI. The mean clear sky index (CSI) and solar variability are found to be correlated with the cloud types and layers with different magnitudes.

The third part demonstrates that the spatial distribution of clouds around San Antonio and beyond shows regional differences in the frequency of cloud-type and cloud-layer occurrence. The highest monthly solar energy values derived from satellite Gs are in the 151-247 kWhm-2 range in July and the lowest in the 43-145 kWhm-2 range in December over the study area (Texas and surrounding areas). The highest seasonal solar potential is found in summer around 457-706 kWhm-2 and the lowest 167-481 kWhm-2 in winter. The annual solar energy potential is 1295-2324 kWhm-2. The solar potential is higher over the ocean than over the land. These findings are useful for the placement of photovoltaic systems and the energy management of smart grids.

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Department

Civil and Environmental Engineering