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theses

Solar energy as a viable renewable energy source has been gaining traction over the past decade, with solar energy claiming the title of fastest growing renewable energy for the past three consecutive years. The significant increase in new installed photovoltaic (PV) capacity can be attributed to plummeting costs of PV modules along with government tax incentive programs. Meanwhile, the cost of land, on which most solar arrays are constructed, has been rising. Thus, careful consideration must be taken when designing large solar panel arrays, both in terms of land use and panel-incident solar energy, so that the array is best tuned to the local radiation field and can harvest the highest amount of incoming solar radiation per unit area.

This dissertation first investigates the complex radiation field across the United States by evaluating data from the National Solar Radiation Database (NSRDB), which is a spatially dense modeled radiation dataset intended to accurately represent long-term statistics. The spatial and temporal characteristics of the direct-beam and diffuse radiation fields across the United States (US) were analyzed. A high proportion of diffuse radiation across the Eastern US and Pacific Northwest underlined the importance of harvesting procedures being better tuned to account for the diffuse field and partly cloudy climates.

Next, an alternative approach of organizing large solar panel arrays is suggested which considers the co-optimization problem of maximizing per-panel incident energy and minimizing the amount of land required. This approach introduces a new dual-angle technique, called the dual-angle solar harvest (DASH) method, in which a solar array is composed of two tilt angles. Results from the DASH method are explored nationwide and for two climatically different locations of Akron, OH and Barstow, CA. For a 10% gain in array-wide plane-of-array incident solar energy when keeping one angle constrained at the single optimum tilt angle, only 35% of panel rows would need to be adjusted in Akron, compared to 70% of rows in Barstow. Thus, it is shown that the DASH method performs best in cloudier locations, such as the Pacific Northwest and the Great Lakes region.

Finally, observed inverter-level energy output data from two solar carport canopies with the same tilt but different azimuth angles on Livingston Campus at Rutgers University are evaluated. The differences in time-of-day energy output are investigated with respect to cloud cover and diurnal variations in the diffuse field, as New Jersey is a partly cloudy climate with a high proportion of diffuse radiation. The inverter-level energy output from the solar canopies are compared to observed solar irradiance data from a nearby meteorological and radiation station (the Rutgers’ Photochemical Assessment Monitoring [PAM] Site) and longer range standardized historical data provided by NREL (TMY3). A sky cover algorithm is also developed to classify days as clear, variable, or cloudy to show that increased cloudiness in the afternoon observed on clear and variable days contributes to differences in the rate of energy output in the morning hours versus afternoon hours between the two solar carport canopies.

ETD_10436

Ph.D.

Includes bibliographical references

doi:10.7282/t3-5fq5-zk70

ETD doctoral

The author owns the copyright to this work.