Abstract

As we drain the Earth's fossil fuels, climate change increasingly puts pressure on scientists to find a cost-efficient renewable energy solution. A nation-wide system using weather resources already in place in combination with the construction of transmission lines and new electricity producing sites is proposed by mentor Chris Clack and associates. The model created optimizes this system with the projected electric load from 2006-2008. Real world publicly accessible solar data was collected and analyzed from ten sites across the contiguous U.S. Corresponding estimation data was computed by the model for solar and collected for comparison. The observation data had been recorded multiple times per hour, and was averaged over the top of the hour to be compared with the hourly model data. Results showed that observation data generally fit well with model data. Correlation coefficients range from .85 to .96 for Global shortwave broadband irradiation. The model was found to perform more effectively in summer months compared to winter months. This was to be expected, as more cloud interference is present throughout the winter compared to summer. The investigation has built accreditation for the wind and solar computer model, and has also provided a larger pool of data to use in the regression.

Mentor

Christopher Clack

Lab site

National Oceanic Atmospheric Administration Earth Systems Research Laboratory (NOAA ESRL)

Funding Acknowledgement

This material is based upon work supported by the S.D. Bechtel, Jr. Foundation and by the National Science Foundation under Grant No. 0952013 and Grant No. 0833353. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the S.D. Bechtel, Jr. Foundation or the National Science Foundation. This project has also been made possible with support of the National Marine Sanctuary Foundation. The STAR program is administered by the Cal Poly Center for Excellence in Science and Mathematics Education (CESaME) on behalf of the California State University (CSU).

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URL: https://digitalcommons.calpoly.edu/star/224

 

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